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The turbine disc plays a crucial role in aerospace engine, significantly influencing both their fatigue life and overall reliability. Due to the substantial uncertainties present, devising a method for the probabilistic analysis of turbine disc fatigue life becomes crucial. This paper introduces a novel framework that combines adaptive Kriging Monte Carlo simulation (AK‐MCS) with a mean stress correction model to evaluate fatigue life distribution effectively. AK‐MCS, stands out as an algorithm that constructs a Kriging model, effectively reducing the need for an extensive finite element analysis. Furthermore, a mean stress correction model is proposed for the Masson‐Coffin equation tailored for fatigue life prediction of GH4133 disc material. This model has been empirically validated to be effective. The presented framework for probabilistic fatigue life analysis not only holds considerable engineering value but also offers innovative approaches for tackling analogous challenges in the field. [ABSTRACT FROM AUTHOR]

The load history exerts a considerable impact on the low cycle fatigue (LCF) life of turbine discs. Thus, oversimplifying the load history leads to substantial errors in fatigue life prediction. This study introduces a probabilistic fatigue life prediction method for turbine discs, accounting for the randomness inherent in LCF load history. The method involves quantifying the randomness of load history through numerical simulation and employing a surrogate model enhanced with learning functions to balance computational efficiency and accuracy. The probabilistic LCF life prediction of full‐scale turbine disc was conducted, demonstrating that the fatigue life scatter predicted by the proposed method more closely aligns with experimental data compared to the original approach. By refining the numerical simulation process, the proposed method better accounts for uncertainties in load history while maintaining computational efficiency, offering significant insights for the fatigue reliability design of turbine discs. [ABSTRACT FROM AUTHOR]

Dynamic fault tree (DFT) is a reliable method for modeling complex systems with dynamic characteristics. However, evaluating the reliability of such systems can be complex. The sequential binary decision diagram (SBDD) method simplifies this process by reducing computational complexity. This study investigates factors influencing SBDD size and proposes a new method, the complete priority ordering method, for ordering basic events in SBDDs. Results demonstrate the method's effectiveness in comparison to existing approaches. [ABSTRACT FROM AUTHOR]

Background: This paper reports a rare presentation of multiple pulp stones (PSs) emerging in all teeth during mixed dentition. It offers valuable insights into the clinical diagnosis, treatment, and prognosis of multiple PSs, shedding light on their occurrence during the mixed dentition period., Case Summary: A 10-year-old girl presented with repeated pain in the mandibular right posterior teeth. Intraoral examination revealed carious lesions, abnormal tooth shapes, and anomalies in tooth number. Radiographic examinations showed multiple PSs with diverse shapes, sizes, and quantities in all teeth, alongside anomalies in tooth shape and number. Root canal therapy was initiated, but the patient initially lacked timely follow-up. Upon return for treatment completion, an extracted tooth revealed irregular calculus within the pulp cavity., Conclusion: This case underscores the importance of considering multiple PSs in mixed dentition, necessitating comprehensive evaluation and management strategies., Competing Interests: Conflict-of-interest statement: The authors declare that they have no competing interests to disclose., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

Of the complex causes of testicular pain, intervertebral disc degeneration is a nonnegligible one, which, however, often fails to get sufficient attention from doctors in clinical practice and consequently leads to misdiagnosis or missed diagnosis. This paper presents an overview of the pathogenesis and treatment of intervertebral disc-induced testicular pain in traditional Chinese and Western medicine, aiming to improve clinicians' understanding of this problem and provide some reference for the diagnosis and treatment of unexplained testicular pain. According to traditional Chinese medicine, the pathogenesis of intervertebral disc-induced testicular pain may be associated with exogenous cold and dampness, damp-heat invasion of Yin organs, qi and blood stagnation, and closely related to the liver, kidney and governor meridian. Western medicine believes that its pathogenesis may be related to nerve root stimulation, nerve root entrapment, Waller degeneration, referred pain, nerve hypersensitivity and other factors.

Protein citrullination is an irreversible post-translational modification process regulated by peptidylarginine deiminases (PADs) in the presence of Ca 2+ . This process is closely related to the occurrence and development of autoimmune diseases, cancers, neurological disorders, cardiovascular and cerebrovascular diseases, and other major diseases. The analysis of protein citrullination by biomass spectrometry confronts great challenges owing to its low abundance, lack of affinity tags, small mass-to-charge ratio change, and susceptibility to isotopic and deamidation interferences. The methods commonly used to study the protein citrullination mainly involve the chemical derivatization of the urea group of the guanine side chain of the peptide to increase the mass-to-charge ratio difference of the citrullinated peptide. Affinity-enriched labels are then introduced to effectively improve the sensitivity and accuracy of protein citrullination by mass spectrometry. 2,3-Butanedione or phenylglyoxal compounds are often used as derivatization reagents to increase the mass-to-charge ratio difference of the citrullinated peptide, and the resulting derivatives have been observed to contain α -dicarbonyl structures. To date, however, no relevant studies on the reactivity of dicarbonyl compounds with citrullinated peptides have been reported. In this study, we determined whether six α -dicarbonyl and two β -dicarbonyl compounds undergo derivatization reactions with standard citrullinated peptides using matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS). Among the α -dicarbonyl compounds, 2,3-butanedione and glyoxal reacted efficiently with several standard citrullinated peptides, but yielded a series of by-products. Phenylglyoxal, methylglyoxal, 1,2-cyclohexanedione, and 1,10-phenanthroline-5,6-dione also derivated efficiently with standard citrullinated peptides, generating a single derivative. Thus, a new derivatization method that could yield a single derivative was identified. Among the β -dicarbonyl compounds, 1,3-cyclohexanedione and 2,4-pentanedione successfully reacted with the standard citrullinated peptides, and generated a single derivative. However, their reaction efficiency was very low, indicating that the β -dicarbonyl compounds are unsuitable for the chemical derivatization of citrullinated peptides. The above results indicate that the α -dicarbonyl structure is necessary for realizing the efficient and specific chemical derivatization of citrullinated peptides. Moreover, the side chains of the α -dicarbonyl structure determine the structure of the derivatives, derivatization efficiency, and generation (or otherwise) of by-products. Therefore, the specific enrichment and precise identification of citrullinated peptides can be achieved by synthesizing α -dicarbonyl structured compounds containing affinity tags. The proposed method enables the identification of citrullinated proteins and their modified sites by MS, thereby providing a better understanding of the distribution of citrullinated proteins in different tissues. The findings will be beneficial for studies on the mechanism of action of citrullinated proteins in a variety of diseases.

Background: Thrombolytic therapy is essential for acute ischemic stroke (AIS) management but poses a risk of hemorrhagic transformation (HT), necessitating accurate prediction to optimize patient care. Methods: A comprehensive search was conducted across PubMed, Web of Science, Scopus, Embase, and Google Scholar, covering studies from inception until July 10, 2024. Studies were included if they used machine learning (ML) or deep learning algorithms to predict HT in AIS patients treated with thrombolysis. Exclusion criteria included studies involving endovascular treatments and those not evaluating model effectiveness. Data extraction and quality assessment were performed following PRISMA guidelines and using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) and Prediction Model Risk of Bias Assessment Tool (PROBAST) tools. Results: Out of 1943 identified records, 12 studies were included in the final analysis, encompassing 18 007 AIS patients who received thrombolytic therapy. The ML models demonstrated high predictive performance, with pooled area under the curve (AUC) values ranging from 0.79 to 0.95. Specifically, XGBoost models achieved AUCs of up to 0.953 and Artificial Neural Network (ANN) models reached up to 0.942. Sensitivity and specificity varied significantly, with the highest sensitivity at 0.90 and specificity at 0.99. Significant predictors of HT included age, glucose levels, NIH Stroke Scale (NIHSS) score, systolic and diastolic blood pressure, and radiomic features. Despite these promising results, methodological disparities and limited external validation highlighted the need for standardized reporting and further rigorous testing. Conclusion: ML techniques, especially XGBoost and ANN, show great promise in predicting HT following thrombolysis in AIS patients, enhancing risk stratification and clinical decision-making. Future research should focus on prospective study designs, standardized reporting, and integrating ML assessments into clinical workflows to improve AIS management and patient outcomes., Competing Interests: Declaration of Conflicting InterestsThe authors declare that there are potential conflicts of interest with respect to the research, authorship, and publication of this article.