Publications by authors named "Y C Xu"

Minute pulmonary meningothelial-like nodules (MPMNs) are benign small lesions in the lungs, with similar pathological characteristics to the meningeal epithelium. MPMNs have similar imaging manifestations to malignant tumors, which can lead to misdiagnosis in clinical practice. There is no consensus on the pathogenesis of MPMNs, with some suggest that MPMNs derive from reactive proliferation, while others suggest that MPMNs share a common origin and molecular mechanism with meningiomas in the central nervous system. Understanding the characteristics of MPMNs and studying their pathogenesis will help improve the understanding and diagnosis of MPMNs. In this article, we reviewed the clinical, pathological, imaging characteristics, differential diagnosis and pathogenesis of MPMNs. We also analyze the existing research advances regarding the pathogenesis and propose prospects for further research.
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Background: Immunoblockade therapy based on the PD-1 checkpoint has greatly improved the survival rate of patients with skin cutaneous melanoma (SKCM). However, existing anti-PD-1 therapeutic efficacy prediction markers often exhibit a poor situation of poor reliability in identifying potential beneficiary patients in clinical applications, and an ideal biomarker for precision medicine is urgently needed.

Methods: 10 multicenter cohorts including 4 SKCM cohorts and 6 immunotherapy cohorts were selected. Through the analysis of WGCNA, survival analysis, consensus clustering, we screened 36 prognostic genes. Then, ten machine learning algorithms were used to construct a machine learning-derived immune signature (MLDIS). Finally, the independent data sets (GSE22153, GSE54467, GSE59455, and in-house cohort) were used as the verification set, and the ROC index standard was used to evaluate the model.

Results: Based on computing framework, we found that patients with high MLDIS had poor overall survival and has good prediction performance in all cohorts and in-house cohort. It is worth noting that MLDIS performs better in each data set than almost all models which from 51 prognostic signatures for SKCM. Meanwhile, high MLDIS have a positive prognostic impact on patients treated with anti-PD-1 immunotherapy by driving changes in the level of infiltration of immune cells in the tumor microenvironment. Additionally, patients suffering from SKCM with high MLDIS were more sensitive to immunotherapy.

Conclusions: Our study identified that MLDIS could provide new insights into the prognosis of SKCM and predict the immunotherapy response in patients with SKCM.

Background: Major incidents (MIs) are an important cause of death and disability. Triage tools are crucial to identifying priority 1 (P1) patients-those needing time-critical, life-saving interventions. Existing expert opinion-derived tools have limited evidence supporting their use. This study employs machine learning (ML) to develop and validate models for novel primary and secondary triage tools.

Methods: Adults (16+ years) from the UK Trauma Audit and Research Network (TARN) registry (January 2008-December 2017) served as surrogates for MI victims, with P1 patients identified using predefined criteria. The TARN database was split chronologically into model training and testing (70:30) datasets. Input variables included physiological parameters, age, mechanism and anatomical location of injury. Random forest, extreme gradient boosted tree, logistic regression and decision tree models were trained to predict P1 status, and compared with existing tools (Battlefield Casualty Drills (BCD) Triage Sieve, CareFlight, Modified Physiological Triage Tool, MPTT-24, MSTART, National Ambulance Resilience Unit Triage Sieve and RAMP). Primary and secondary candidate models were selected; the latter was externally validated on patients from the UK military's Joint Theatre Trauma Registry (JTTR).

Results: Models were internally tested in 57 979 TARN patients. The best existing tool was the BCD Triage Sieve (sensitivity 68.2%, area under the receiver operating curve (AUC) 0.688). Inability to breathe spontaneously, presence of chest injury and mental status were most predictive of P1 status. A decision tree model including these three variables exhibited the best test characteristics (sensitivity 73.0%, AUC 0.782), forming the candidate primary tool. The proposed secondary tool (sensitivity 77.9%, AUC 0.817), applicable via a portable device, includes a fourth variable (injury mechanism). This performed favourably on external validation (sensitivity of 97.6%, AUC 0.778) in 5956 JTTR patients.

Conclusion: Novel triage tools developed using ML outperform existing tools in a nationally representative trauma population. The proposed primary tool requires external validation prior to consideration for practical use. The secondary tool demonstrates good external validity and may be used to support decision-making by healthcare workers responding to MIs.

MicroRNAs belong to the family of non-coding RNAs that participate in cell proliferation, cell death and development. The Müller glial cells are the inherent and specific neuroglia cells in the retinal organisation and play significant roles in retinal neuroprotection, organisational maintenance, inflammation and immunity, regeneration, and the occurrence and development of retinal diseases. However, only a few studies report the underlying mechanism of how miRNAs drive the function of Müller glial cells in the development of retinal diseases. This review aims to summarise the roles of miRNAs in retinal Müller glial cell function, including gliogenesis, inflammation and immunity, regeneration, the development of retinal diseases, and retinal development. This review may point out a novel miRNA-based insight into retinal repair and regeneration. MiRNAs in Müller glial cells may be considered a diagnostic and therapeutic target in the process of retinal repair and regeneration.

Deep eutectic solvents (DESs) have emerged as promising and eco-friendly solvents for the efficient extraction of lignin from biomass due to their low cost and environmental benefits. Nevertheless, the prevalent use of acidic DESs in lignin extraction often results in excessive depolymerization and recondensation of lignin, thereby impeding its downstream applications. In this study, we developed a range of alkaline DESs (ADESs), both pure and peroxide-containing, for the extraction of high-quality lignin from bamboo. Moreover, carbon dioxide (CO) was employed for the precipitation and regeneration of the extracted lignin. The obtained lignin fractions were comprehensively characterized in terms of yield, purity, morphology, solubility, structural features, and anti-UV/oxidant activity. The results showed that the monoethanolamine-based ADES demonstrated superior performance among the pure ADESs. Structural analysis confirmed the well-preserved substructures of lignin fractions obtained using ADESs, with β-O-4 bond retention ranging from 49.8 % to 68.4 %. The incorporation of a suitable amount of peroxide improved lignin yield, morphology, solubility, and anti-UV/oxidant activity. Additionally, the anti-UV/oxidant activity of lignin exhibited a positive correlation with its phenolic hydroxyl content. This study provides a valuable reference for the green and sustainable production and valorization of lignin within the existing biorefinery framework.