Thyroid cancer is a common clinical disease, and surgical resection remains the primary treatment modality, generally yielding a favorable prognosis. However, postoperative infections and related complications not only adversely affect patient outcomes but also prolong hospital stays, increase medical expenses, and impair quality of life. Therefore, effective prevention and management of postoperative infections have become urgent clinical priorities. Based on recent literature, this review summarizes the prevention, treatment, and current research progress regarding postoperative infections following thyroid cancer surgery. The aim is to provide evidence for the early detection, accurate diagnosis, and timely intervention of postoperative infections in patients with thyroid cancer.

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This dissertation investigates the extent to which TP53 mutations influence the efficacy of targeted therapies (EGFR-TKIs, ALK-TKIs, and ROS1-TKIs) in the treatment of Non-Small Cell Lung Cancer (NSCLC), which accounts for 85% of all lung cancer cases. To address the core research question, the study adopts a systematic literature review approach, synthesizing data from peer-reviewed clinical studies, meta-analyses, and guidelines published by authoritative bodies such as the FDA and EMA. The research focuses on three main themes: the functional mechanisms of TP53 mutations in driving treatment resistance, the quantitative impact of these mutations on important efficacy parameters (Progression-Free Survival [PFS] and Objective Response Rate [ORR]) across different targeted therapies, and the clinical consequences of TP53 testing for personalized treatment stratification. Key findings show that TP53 mutations exert a moderate-to-strong negative effect on targeted therapy outcomes: reducing ORR by 25 47% and decreasing PFS by 35 63% throughout EGFR, ALK, and ROS1-TKIs. Mechanistically, mutations impair DNA repair, promote tumor angiogenesis, and inhibit apoptosis, whereas a significant exception is the combination of EGFR-TKIs with anti-angiogenic inhibitors, which reduces this effect in select EGFR-positive patients. The study concludes that TP53 mutations are important drivers of lower targeted therapy efficacy, and combining TP53 testing as a complementary biomarker might guide clinical decision-making. However, standardised mutation detection protocols and bigger prospective trials are needed to corroborate findings, particularly for ROS1-TKI therapy and subtype-specific analyses.

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Objective: To investigate the key influencing factors and complex interaction patterns associated with Cerebral Small Vessel Disease (CSVD) in patients with carotid plaque, and to construct a high-accuracy and highly interpretable CSVD risk prediction model. Methods: A retrospective case–control study was conducted, enrolling 373 patients with carotid plaque (207 CSVD-positive and 166 CSVD-negative cases). Demographic data, inflammatory biomarkers, and lipid profile indicators were collected. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection, and multivariate logistic regression was applied to identify independent risk factors. Restricted Cubic Spline (RCS) analysis was performed to assess potential nonlinear relationships between continuous variables and CSVD risk. Four machine learning algorithms—Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Partial Least Squares Discriminant Analysis (PLS-DA), and XGBoost—were used to develop predictive models. The optimal model was further interpreted using the SHapley Additive exPlanations (SHAP) framework to provide both global and local explanations. Results: Multivariate logistic regression showed that age (OR = 1.09), Neutrophil count (N) (OR = 1.87), Low-Density Lipoprotein (LDL) (OR = 1.78), very low-density lipoprotein (VLDL) (OR = 2.24), and Atherogenic Index of Plasma (AIP) (OR = 2.95) were independent risk factors for CSVD, while High-Density Lipoprotein (HDL) was a protective factor (OR = 0.33). RCS analysis revealed a J-shaped relationship between age and CSVD risk, and an inverted U-shaped relationship between VLDL and risk. Among the machine learning models, XGBoost achieved the best performance, with an AUC of 0.917 in the test set (95% CI: 0.866–0.969). SHAP analysis identified age as the most important global predictor and enabled visualization of individual patient-level risk-driving and protective factors. Conclusion: Aging, neutrophil-mediated inflammatory response, and an atherogenic lipid profile are independent risk factors for CSVD in patients with carotid plaque. Significant nonlinear effects were observed for age and VLDL. The XGBoost-based predictive model demonstrates excellent performance, and integration with the SHAP interpretability framework provides precise and intuitive decision support for early risk stratification and individualized intervention in CSVD.

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Current Parkinson's Disease (PD) treatments alleviate symptoms but do not halt progression from degeneration of A9 dopaminergic neurons in substantia nigra pars compacta. Human induced Pluripotent Stem Cells (iPSCs)-based cell replacement therapy has emerged as a promising therapy to PD, but it still faces two significant challenges. One of them is that it is difficult to generate sufficient high-purity and functional A9 neurons effectively; the other is that transplanted neurons readily perish in the hostile brain milieu, which significantly suppresses therapeutic actions. This review presents the fundamental molecular pathways regulating the differentiation of human iPSCs into A9-type dopaminergic neurons in a directional manner. It addresses the systematic control of Shh, Wnt/β-catenin, and SMAD signal transduction, and significant transcription factors such as FoxA2, Lmx1a/b, Nurr1, and Pitx3, a collective of which plays a crucial role in defining the distinct molecular attributes of the A9 neurons. Two practical and efficient differentiation protocols are summarized: a pretreatment system using three small molecules based on CTraS, and an optimized induction strategy targeting SHH/Wnt signaling pathways. Moreover, this review illustrates the fundamental mechanism of neuron apoptosis focusing on mitochondrial pathway and details two viable approaches to enhance the anti-apoptotic ability of A9 neurons via activating Nur77-PARL-BCL-2 signal pathway and enhancing expression of miR-221. Finally, the new concept of functionalization based on efficient differentiation and anti-apoptotic modification proposed in this review is expected to yield ideal high-yield, purity and survival robust A9 neurons. This review refers to theoretical delivery and clinical strategies for stimulating the use of iPSC-based PD cell therapy.

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