15 results on '"Kurata, H."'
Search Results
2. Association of fish intake with all-cause mortality according to CRP levels or inflammation in older adults: a prospective cohort study.
- Author
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Kurata H, Meguro S, Abe Y, Sasaki T, Arai Y, and Hayashi K
- Subjects
- Humans, Female, Male, Prospective Studies, Aged, 80 and over, Animals, Diet, Seafood, Cause of Death, Japan epidemiology, Fishes, C-Reactive Protein analysis, Inflammation blood, Inflammation mortality, Mortality trends
- Abstract
Background: The relationship between inflammatory response, fish consumption, and mortality risk in older individuals is unclear. We investigated whether C-reactive protein (CRP) levels ≥ 0.1 mg/dL, fish intake, and inflammatory responses are associated with all-cause mortality risk in older adults., Methods: This prospective cohort study included older adults aged 85-89 years from the Kawasaki Aging and Wellbeing Project, who did not require daily care. Cohort was recruited from March 2017 to December 2018 (follow-up ended on December 31, 2021). Dietary assessment was conducted using the Brief Self-Administered Diet History Questionnaire. Multivariate Cox proportional hazards regression was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) for all-cause mortality in the CRP ≥ 0.1 mg/dL group; the CRP < 0.1 mg/dL group was used for reference. Within CRP ≥ 0.1 and < 0.1 mg/dL groups, participants were categorized into tertiles of fish intake. HRs and 95% CIs for all-cause mortality in the other groups were estimated using the lower tertile group as a reference., Results: The study included 996 participants (mean [standard deviation] age, 86.5 [1.37] years; 497 [49.9%] women) with a median CRP level of 0.08 (interquartile range [IQR] = 0.04-0.16). There were 162 deaths during 4,161 person-years of observation; the multivariable-adjusted HR for all-cause mortality in the CRP ≥ 0.1 mg/dL group was 1.86 (95% CI, 1.32-2.62); P < 0.001. In 577 individuals with median (IQR) fish intake of 39.3 g/1000 kcal (23.6-57.6) and CRP level of < 0.1 mg/dL, the multivariable-adjusted HR for all-cause mortality in the higher tertile group of fish intake was 1.15 (0.67-1.97); P = 0.59, non-linear P = 0.84. In 419 individuals with median (IQR) fish intake of 40.7 g/1000 kcal (25.0-60.1) and CRP level of ≥ 0.1 mg/dL, the multivariate-adjusted HR for all-cause mortality in the higher tertile group of fish intake was 0.49 (0.26-0.92); P = 0.026, non-linear P = 0.38, P-value for interaction = 0.040., Conclusions: A negative association between fish intake and all-cause mortality was seen in older adults with elevated CRP levels, which is a mortality risk factor. While the results may be limited owing to stringent methods ensuring impartiality, they offer valuable insights for future research., Trial Registration: UMIN000026053. Registered February 24, 2017., (© 2024. The Author(s).)
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- 2024
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3. Journal of Medicinal Chemistry Collection: Drug Discovery in Japan.
- Author
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Suzuki T, Kurata H, Ohwada T, and Onodera H
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- Japan, Humans, Periodicals as Topic, Drug Discovery methods, Chemistry, Pharmaceutical methods
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- 2024
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4. PredIL13: Stacking a variety of machine and deep learning methods with ESM-2 language model for identifying IL13-inducing peptides.
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Kurata H, Harun-Or-Roshid M, Tsukiyama S, and Maeda K
- Subjects
- Humans, Computational Biology methods, COVID-19 immunology, Logistic Models, Machine Learning, Software, Deep Learning, Interleukin-13 metabolism, Peptides
- Abstract
Interleukin (IL)-13 has emerged as one of the recently identified cytokine. Since IL-13 causes the severity of COVID-19 and alters crucial biological processes, it is urgent to explore novel molecules or peptides capable of including IL-13. Computational prediction has received attention as a complementary method to in-vivo and in-vitro experimental identification of IL-13 inducing peptides, because experimental identification is time-consuming, laborious, and expensive. A few computational tools have been presented, including the IL13Pred and iIL13Pred. To increase prediction capability, we have developed PredIL13, a cutting-edge ensemble learning method with the latest ESM-2 protein language model. This method stacked the probability scores outputted by 168 single-feature machine/deep learning models, and then trained a logistic regression-based meta-classifier with the stacked probability score vectors. The key technology was to implement ESM-2 and to select the optimal single-feature models according to their absolute weight coefficient for logistic regression (AWCLR), an indicator of the importance of each single-feature model. Especially, the sequential deletion of single-feature models based on the iterative AWCLR ranking (SDIWC) method constructed the meta-classifier consisting of the top 16 single-feature models, named PredIL13, while considering the model's accuracy. The PredIL13 greatly outperformed the-state-of-the-art predictors, thus is an invaluable tool for accelerating the detection of IL13-inducing peptide within the human genome., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Kurata et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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- 2024
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5. Conditions for late gadolinium enhancement MRI in myocardial infarction model rats that better reflect microscopic tissue staining.
- Author
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Ueda J, Kurata H, Ota M, Yabata I, Itagaki K, Sawaya R, Murata C, Banura N, Nishida H, and Saito S
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- Animals, Rats, Male, Staining and Labeling methods, Myocardium pathology, Rats, Sprague-Dawley, Myocardial Infarction diagnostic imaging, Myocardial Infarction pathology, Gadolinium, Disease Models, Animal, Magnetic Resonance Imaging methods, Contrast Media
- Abstract
Late gadolinium enhancement (LGE) is a widely used magnetic resonance imaging method for assessing cardiac disease. However, the relationship between different LGE signal thresholds and microscopic tissue staining images is unclear. In this study, we performed cardiovascular MRI on myocardial infarction (MI) model rats and evaluated the relationship between LGE with different signal thresholding methods and tissue staining images. We prepared 16 rats that underwent MRI 14-18 days following a surgery to create an MI model. We captured cine and LGE images of the cardiac short-axis and longitudinal two- and four-chamber views. The mean ± 2SD, ± 3SD, and ± 5SD of the pixel values in the non-infarcted area were defined as the LGE area. We compared areas of Sirius red staining, determined by the color tone, with their respective LGE areas at end-diastole and end-systole. We observed that the LGE area calculated as the mean ± 2SD of the non-infarcted area at end-diastole demonstrated a significant positive correlation with the area of Sirius red staining (Pearson's correlation coefficient in both: 0.81 [p < 0.01]). Therefore, the LGE area calculated as the mean ± 2SD of the non-infarcted area at end-diastole best reflected the MI area in tissue staining., (© 2024. The Author(s).)
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- 2024
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6. High serum gamma-glutamyltransferase level after hepatitis C virus elimination is a risk factor for the development of hepatocellular carcinoma.
- Author
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Murakawa M, Nakagawa M, Nishimura H, Kaneko S, Miyoshi M, Kawai-Kitahata F, Nitta S, Tsuchiya J, Shimizu T, Watakabe K, Mochida T, Inada K, Iizuka Y, Sakai H, Sakurai Y, Sato A, Azuma S, Kawamura T, Maeyashiki C, Kurosaki M, Kusano F, Watanabe H, Kurata H, Karakama Y, Fujiwara T, Nagata Y, Tanaka T, Kakinuma S, Okamoto R, and Asahina Y
- Abstract
Aim: Gamma-glutamyltransferase (GGT) is known as an oxidative stress marker, induced by alcohol consumption and metabolic disorders, and is reported as a predictor of hepatocellular carcinoma (HCC) development after hepatitis C virus (HCV) elimination. However, it is not clear whether GGT serves simply as a surrogate marker for overlapping metabolic diseases or reflects HCV-specific carcinogenicity. We investigated the association between GGT and hepatocarcinogenesis after achieving a sustained viral response (SVR), accounting for drinking habits or diabetes, and examined predisposing factors associated with GGT levels after SVR., Methods: This is a prospective, multicenter, and observational study using the database of 1001 patients after HCV eradication with direct-acting antiviral agents. The association of GGT at SVR with cumulative HCC development was examined in a multivariate analysis using Cox proportional hazard models after adjustment for covariates including alcohol and diabetes. The association between oxidative stress markers or genetic factors and GGT levels was analyzed., Results: High GGT levels at SVR were associated with HCC development (HR] 2.38, 95% CI 1.10-5.17). This association was also significant when restricted to patients without alcohol consumption or diabetes (HR 8.38, 95% CI 2.87-24.47). GGT levels were correlated with serum growth differentiation factor 15 levels, a marker of mitochondrial dysfunction. Single-nucleotide polymorphisms of ZNF827 and GDF15 were associated with high GGT levels., Conclusions: High GGT levels at SVR were associated with HCC development after accounting for alcohol consumption and diabetes. GGT levels are influenced by genetic predisposition and may reflect mitochondrial dysfunction after HCV eradication., (© 2024 Japan Society of Hepatology.)
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- 2024
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7. Predictive Factors for Early Biochemical Recurrence Following Robot-assisted Radical Prostatectomy.
- Author
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Mitsunari K, Fukushima H, Kurata H, Harada J, Nakamura Y, Matsuo T, Ohba K, Mochizuki Y, and Imamura R
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- Humans, Male, Middle Aged, Aged, Retrospective Studies, Risk Factors, Margins of Excision, Prostatectomy methods, Prostate-Specific Antigen blood, Prostatic Neoplasms surgery, Prostatic Neoplasms pathology, Prostatic Neoplasms blood, Neoplasm Grading, Robotic Surgical Procedures methods, Neoplasm Recurrence, Local pathology, Neoplasm Recurrence, Local blood, Neoplasm Staging
- Abstract
Background/aim: The primary objective of this study was to identify predictors for biochemical recurrence (BCR) within 2 years following robot-assisted radical prostatectomy (RARP). Identifying predictors will enable insights that enhance personalized patient management and facilitate the ongoing refinement of postoperative therapy strategies., Patients and Methods: This retrospective study included patients undergoing RARP from September 2014 to January 2021. Exclusion criteria were preoperative endocrine therapy, BCR beyond 2 years post-surgery, and incomplete postoperative data. Multivariate analyses were conducted to evaluate predictors of BCR, focusing on preoperative prostate-specific antigen (PSA) level, pathological tumor (pT) stage, Gleason score (GS), extraprostatic extension (EPE), and surgical margin status., Results: Among 374 patients, 40 experienced BCR within 2 years. Significant predictors of early BCR included initial PSA level ≥10 ng/ml, pT3 or greater, GS ≥8, EPE, and positive surgical margins (RM1). Multivariate analysis identified pT3 or higher, GS ≥8, and RM1 as independent risk factors for early BCR., Conclusion: Early BCR after RARP is significantly associated with advanced pathological stage, high GS, and positive surgical margins. These findings emphasize the need for tailored postoperative management strategies and highlight the importance of precision in surgical technique to improve patient outcomes., (Copyright © 2024 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)
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- 2024
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8. MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models.
- Author
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Kurata H, Harun-Or-Roshid M, Mehedi Hasan M, Tsukiyama S, Maeda K, and Manavalan B
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- Humans, Computational Biology methods, RNA Processing, Post-Transcriptional, Algorithms, 5-Methylcytosine metabolism, 5-Methylcytosine chemistry, Machine Learning, RNA genetics, RNA chemistry, RNA metabolism
- Abstract
RNA modification serves as a pivotal component in numerous biological processes. Among the prevalent modifications, 5-methylcytosine (m5C) significantly influences mRNA export, translation efficiency and cell differentiation and are also associated with human diseases, including Alzheimer's disease, autoimmune disease, cancer, and cardiovascular diseases. Identification of m5C is critically responsible for understanding the RNA modification mechanisms and the epigenetic regulation of associated diseases. However, the large-scale experimental identification of m5C present significant challenges due to labor intensity and time requirements. Several computational tools, using machine learning, have been developed to supplement experimental methods, but identifying these sites lack accuracy and efficiency. In this study, we introduce a new predictor, MLm5C, for precise prediction of m5C sites using sequence data. Briefly, we evaluated eleven RNA sequence-derived features with four basic machine learning algorithms to generate baseline models. From these 44 models, we ranked them based on their performance and subsequently stacked the Top 20 baseline models as the best model, named MLm5C. The MLm5C outperformed the-state-of-the-art predictors. Notably, the optimization of the sequence length surrounding the modification sites significantly improved the prediction performance. MLm5C is an invaluable tool in accelerating the detection of m5C sites within the human genome, thereby facilitating in the characterization of their roles in post-transcriptional regulation., Competing Interests: Declaration of competing interest The authors 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.)
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- 2024
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9. Meta-2OM: A multi-classifier meta-model for the accurate prediction of RNA 2'-O-methylation sites in human RNA.
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Harun-Or-Roshid M, Pham NT, Manavalan B, and Kurata H
- Subjects
- Humans, Methylation, Machine Learning, Software, Computational Biology methods, RNA genetics, RNA chemistry, Algorithms
- Abstract
2'-O-methylation (2-OM or Nm) is a widespread RNA modification observed in various RNA types like tRNA, mRNA, rRNA, miRNA, piRNA, and snRNA, which plays a crucial role in several biological functional mechanisms and innate immunity. To comprehend its modification mechanisms and potential epigenetic regulation, it is necessary to accurately identify 2-OM sites. However, biological experiments can be tedious, time-consuming, and expensive. Furthermore, currently available computational methods face challenges due to inadequate datasets and limited classification capabilities. To address these challenges, we proposed Meta-2OM, a cutting-edge predictor that can accurately identify 2-OM sites in human RNA. In brief, we applied a meta-learning approach that considered eight conventional machine learning algorithms, including tree-based classifiers and decision boundary-based classifiers, and eighteen different feature encoding algorithms that cover physicochemical, compositional, position-specific and natural language processing information. The predicted probabilities of 2-OM sites from the baseline models are then combined and trained using logistic regression to generate the final prediction. Consequently, Meta-2OM achieved excellent performance in both 5-fold cross-validation training and independent testing, outperforming all existing state-of-the-art methods. Specifically, on the independent test set, Meta-2OM achieved an overall accuracy of 0.870, sensitivity of 0.836, specificity of 0.904, and Matthew's correlation coefficient of 0.743. To facilitate its use, a user-friendly web server and standalone program have been developed and freely available at http://kurata35.bio.kyutech.ac.jp/Meta-2OM and https://github.com/kuratahiroyuki/Meta-2OM., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Harun-Or-Roshid et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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- 2024
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10. The 30-second chair stand test (CS30) as a predictor of exercise tolerance in elderly individuals (≥75 years) with stage A/B heart failure.
- Author
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Kobayashi T, Iwasaki T, Kurata H, Nikaido A, and Hata Y
- Abstract
Background: In Japan, the number of very elderly individuals with heart failure (HF) is on the rise. One indicator of HF stage progression is a decrease in exercise tolerance (ET). While peak oxygen uptake (peak VO₂) determined by cardiopulmonary exercise testing (CPX) is the gold standard for ET assessment, the wide-scale applicability of CPX is constrained owing to expensive equipment and challenges in this population. The 30-second chair stand test (CS30), a simple and quick alternative, is widely used among community-dwelling elderly individuals. The objective of this study was to investigate whether CS30 is a predictor of ET in elderly individuals with stage A/B HF., Methods: Of 748 outpatients aged 75 years and over who visited our center between March 2021 and December 2022, 493 patients (296 males and 197 females) were included in this study. CS30 was measured using a seat height of 40 cm, and peak VO₂ was assessed using CPX., Results: The findings showed a statistically significant positive association between CS30 and peak VO₂ for both males and females (males: β = 0.255, 95 % CI = 0.102-0.407; females: β = 0.282, 95 % CI = 0.043-0.521). Receiver operating characteristic (ROC) analyses showed moderate accuracy of CS30 in predicting low ET in both sexes (males AUC = 0.740, 95 % CI = 0.640-0.841, p < 0.001; females AUC = 0.725, 95 % CI = 0.644-0.807, p < 0.001). The cut-off values of CS30 were established as 18 times for males and 16 times for females., Conclusions: CS30 is a potentially convenient method for estimating current ET in older adults, providing a feasible alternative to CPX., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)
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- 2024
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11. Intrinsic Visible Plasmonic Properties of Colloidal PtIn 2 Intermetallic Nanoparticles.
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Takekuma H, Sato R, Iida K, Kawawaki T, Haruta M, Kurata H, Nobusada K, and Teranishi T
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Materials that intrinsically exhibit localized surface plasmon resonance (LSPR) in the visible region have been predominantly researched on nanoparticles (NPs) composed of coinage metals, namely Au, Ag, and Cu. Here, as a coinage metal-free intermetallic NPs, colloidal PtIn
2 NPs with a C1 (CaF2 -type) crystal structure are synthesized by the liquid phase method, which evidently exhibit LSPR at wavelengths similar to face-centered cubic (fcc)-Au NPs. Computational simulations pointed out differences in the electronic structure and photo-excited electron dynamics between C1-PtIn2 and fcc-Au NPs; reduces interband transition and stronger screening with smaller number of bound d-electrons compare with fcc-Au are unique origins of the visible plasmonic nature of C1-PtIn2 NPs. These results strongly indicate that the intermetallic NPs are expected to address the development of alternative plasmonic materials by tuning their crystal structure and composition., (© 2024 The Authors. Advanced Science published by Wiley-VCH GmbH.)- Published
- 2024
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12. Identification of a reliable sacral-sparing examination to assess the ASIA impairment scale in patients with traumatic spinal cord injury.
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Ariji Y, Hayashi T, Ideta R, Koga R, Murai S, Naka T, Ifuku R, Towatari F, Sakai H, Kurata H, and Maeda T
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- Humans, Retrospective Studies, Physical Examination, Paralysis diagnosis, Paralysis etiology, Recovery of Function, Spinal Cord Injuries complications, Spinal Cord Injuries diagnosis, Spinal Injuries
- Abstract
Objectives: We evaluated the time course of the American Spinal Cord Injury Association (ASIA) impairment scale (AIS) for up to three months in participants within 72 h after traumatic spinal cord injury (TSCI) with complete paralysis. We aimed to determine the most useful sacral-sparing examination (deep anal pressure [DAP], voluntary anal contraction [VAC], S4-5 light touch [LT], or pin prick [PP] sensation) in determining AIS grades., Design: Retrospective cohort study., Setting: Spinal Injuries Center, Fukuoka, Japan., Participants: Among 668 TSCI participants registered in the Japan Single Center study for Spinal Cord Injury Database (JSSCI-DB) between January 2012 and May 2020, we extracted the data of 80 patients with AIS grade A within 72 h after injury and neurological level of injury (NLI) at T12 or higher., Interventions: None., Outcome Measures: The sacral-sparing examination at the time of the change to incomplete paralysis was compared to the AIS determination using a standard algorithm and with each assessment including the VAC, DAP, S4-5LT, and S4-5PP examinations at the time of AIS functional change. Agreement among assessments was evaluated using weighted kappa coefficients. The relationship was evaluated using Spearman's rank correlation coefficients., Results: Fifteen participants (18.8%) improved to incomplete paralysis (AIS B to D) within three months after injury. The single assessment among the sacral-sparing examinations with the highest agreement and strongest correlation with AIS determination was the S4-5LT examination ( k = 0.89, P < 0.01, r = 0.84, P < 0.01)., Conclusions: The S4-5LT examination is key in determining complete or incomplete paralysis due to its high discriminatory power.
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- 2024
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13. Efficacy and Safety of Brachytherapy for Localized Prostate Cancer in Renal Transplant Recipients.
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Mitsunari K, Kurata H, Ito I, Harada J, Nakamura Y, Matsuo T, Ohba K, Mochizuki Y, and Imamura R
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- Humans, Male, Prostate-Specific Antigen, Retrospective Studies, Kidney Transplantation adverse effects, Brachytherapy adverse effects, Brachytherapy methods, Prostatic Neoplasms radiotherapy, Prostatic Neoplasms surgery, Prostatic Neoplasms complications
- Abstract
Background: Prostate cancer is common among male renal transplant recipients and can present challenges for medical management and patient survival. It is imperative to have a comprehensive understanding of available treatment options in this population to determine the most effective and safe therapies. Brachytherapy, a safe and effective treatment for localized prostate cancer, has not been sufficiently studied in this patient population. Therefore, this study aimed to evaluate the safety and effectiveness of brachytherapy in treating prostate cancer in renal transplant recipients., Methods: We retrospectively reviewed our brachytherapy database to identify patients with a previous history of renal transplantation who underwent seed implantation for localized prostate cancer. Long-term prostate-specific antigen control and treatment-related toxicity, including graft dysfunction and urinary and rectal complications, were assessed and compared with published outcomes. Results were analyzed to evaluate the efficacy and safety of seed implantation in this patient population., Results: We identified 2 patients with previous renal transplantation who underwent permanent seed implantation for localized prostate cancer. Follow-ups ranged from 53 to 57 months, and both patients remained free of prostate-specific antigen progression with normal graft function. No acute and late complications occurred., Conclusion: Brachytherapy is a safe and effective treatment option for post-renal transplant prostate cancer. Given the paucity of reports on brachytherapy in this population, the findings of this study, despite a small sample size, contribute to the increasing body of evidence supporting the use of brachytherapy in this patient population., Competing Interests: Declaration of competing interest The authors 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.)
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- 2024
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14. Stack-DHUpred: Advancing the accuracy of dihydrouridine modification sites detection via stacking approach.
- Author
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Harun-Or-Roshid M, Maeda K, Phan LT, Manavalan B, and Kurata H
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- RNA, Messenger, Computational Biology, Epigenesis, Genetic, Genome
- Abstract
Dihydrouridine (DHU, D) is one of the most abundant post-transcriptional uridine modifications found in tRNA, mRNA, and snoRNA, closely associated with disease pathogenesis and various biological processes in eukaryotes. Identifying D sites is important for understanding the modification mechanisms and/or epigenetic regulation. However, biological experiments for detecting D sites are time-consuming and expensive. Given these challenges, computational methods have been developed for accurately identifying the D sites in genome-wide datasets. However, existing methods have some limitations, and their prediction performance needs to be improved. In this work, we have developed a new computational predictor for accurately identifying D sites called Stack-DHUpred. Briefly, we trained 66 baseline models or single-feature models by connecting six machine learning classifiers with eleven different feature encoding methods and stacked different baseline models to build stacked ensemble learning models. Subsequently, the optimal combination of the baseline models was identified for the construction of the final stacked model. Remarkably, the Stack-DHUpred outperformed the existing predictors on our new independent dataset, indicating that the stacking approach significantly improved the prediction performance. We have made Stack-DHUpred available to the public through a web server (http://kurata35.bio.kyutech.ac.jp/Stack-DHUpred) and a standalone program (https://github.com/kuratahiroyuki/Stack-DHUpred). We believe that Stack-DHUpred will be a valuable tool for accelerating the discovery of D modifications and understanding their role in post-transcriptional regulation., Competing Interests: Declaration of competing interest All authors declare that they have no conflict of interest., (Copyright © 2023 Elsevier Ltd. All rights reserved.)
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- 2024
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15. Elucidating Key Characteristics of PFAS Binding to Human Peroxisome Proliferator-Activated Receptor Alpha: An Explainable Machine Learning Approach.
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Maeda K, Hirano M, Hayashi T, Iida M, Kurata H, and Ishibashi H
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- Humans, Liver metabolism, PPAR alpha metabolism, Fluorocarbons
- Abstract
Per- and polyfluoroalkyl substances (PFAS) are widely employed anthropogenic fluorinated chemicals known to disrupt hepatic lipid metabolism by binding to human peroxisome proliferator-activated receptor alpha (PPARα). Therefore, screening for PFAS that bind to PPARα is of critical importance. Machine learning approaches are promising techniques for rapid screening of PFAS. However, traditional machine learning approaches lack interpretability, posing challenges in investigating the relationship between molecular descriptors and PPARα binding. In this study, we aimed to develop a novel, explainable machine learning approach to rapidly screen for PFAS that bind to PPARα. We calculated the PPARα-PFAS binding score and 206 molecular descriptors for PFAS. Through systematic and objective selection of important molecular descriptors, we developed a machine learning model with good predictive performance using only three descriptors. The molecular size ( b_single ) and electrostatic properties ( BCUT_PEOE_3 and PEOE_VSA_PPOS ) are important for PPARα-PFAS binding. Alternative PFAS are considered safer than their legacy predecessors. However, we found that alternative PFAS with many carbon atoms and ether groups exhibited a higher affinity for PPARα. Therefore, confirming the toxicity of these alternative PFAS compounds with such characteristics through biological experiments is important.
- Published
- 2024
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