Issue 1 (May)

Papillary thyroid carcinoma (PCT), follicular origin are divided into RAS-like malignancies and BRAF-like malignancies according to their molecular characteristics and aggressiveness. With the continuous development of the molecular level, genetic mutations are significant in the diagnosis, treatment and prognosis of papillary thyroid carcinoma. This paper discusses the latest progress of papillary thyroid cancer gene mutation and its clinical application, in order to provide more efficient diagnosis and treatment means for patients.

Background: Neutrophil lymphocyte ratio (NLR) and platelet lymphocyte ratio (PLR) are biomarkers for the diagnosis and prognosis of many diseases. However, the diagnostic accuracy of IVIG resistant Kawasaki disease is still unclear. This study aims to evaluate the diagnostic value of NLR and PLR in IVIG resistant Kawasaki disease. Method: We used Pubmed, Embase, Web of science, CNKI and Google academic database to find all articles that met the inclusion criteria until January 5 2024.Result: After two independent researchers carefully read the title, abstract, and full text, five eligible studies were included in the study analysis, with a total of 3359 children included. The research results showed that the combined sensitivity and specificity were 0.57 (95% CI: 0.48-0.66) and 0.73 (95% CI: 0.67-0.78), respectively; The pooled positive likelihood ratio and Negative likelihood ratio were2.12（95%CI:1.91-2.34）and 0.58（95%CI:0.50-0.68）, respectively;The pooled DOR was 3.62（95% CI:2.99-4.39）;The area under the SROC curve (AUC) was 0.71 (95% CI: 0.67-0.75), indicating high diagnostic performance. Conclusion: This study analysis indicates that the PLR+NLR levels in children with Kawasaki disease can serve as an important parameter in the risk scoring system, with relatively high accuracy.

Current monitoring systems employing single model algorithms face challenges in accurately recognizing and alerting real-time arrhythmic events in patients with severe cardiac conditions. To address this issue and improve the detection accuracy of electrocardiogram (ECG) monitoring systems, this paper introduces a novel arrhythmia recognition model based on Stacking ensemble learning. This model integrates multiple base learners, including LightGBM, XGBoost, Random Forest, SVM, and Logistic Regression, and optimizes them using Gradient Boosting as the meta-learner. Hyperparameters were fine-tuned through grid search, and nested cross-validation was employed to train the model, ensuring robust predictive performance. The detection results indicate that the Stacking ensemble model significantly outperforms single models in both accuracy and stability, offering substantial practical application value for clinical ECG monitoring and diagnosis.

Background: Observational studies have demonstrated a relationship between leukocyte telomere length (LTL) and psoriasis. However, the causal association between them remains unknown.

Methods: Bidirectional Mendelian randomization (MR) analysis was performed using publicly available genome-wide association study (GWAS) summary statistics. The GWAS summary data involving 472,174 participants for ITL were obtained from the UKbiobank, while the summary data for psoriasis (8,075 cases) and its two main types, psoriasis vulgaris (PsV, 5,018 cases) and psoriatic arthritis (PsA, 2,919 cases) were obtained from the FinnGen consortium. The inverse variance weighted (IVW) method was used as the main analysis.

Results: The forward MR analyses indicated that genetically determined LTL was suggestively associated with psoriasis (IVW: OR: 0.858; 95% CI: 0.752-0.980; P= 0.024) and significantly associated with PsV (IVW: OR: 0.790; 95% CI: 0.671-0.931; P= 0.005), but not with PsA (IVW: OR: 0.845; 95% CI: 0.685-1.043; p= 0.117). The reverse MR analyses showed that no causal effects were observed in psoriasis and its two subtypes on LTL.

Conclusion: Our study suggested a potential causal effect of shortened LTL on the increased risk of psoriasis, especially PsV, providing LTL as a novel biomarker and therapeutic target for psoriasis.

Objective: To establish a model of methicillin-resistant Staphylococcus aureus（MRSA） pneumonia and observe the effect of MRSA on macrophage polarization. Methods: The MRSA pneumonia model is established by adding 1×108CFU/mL MRSA bacterial solution to BALB/c mice through nasal drip. To make pathological specimens of lung tissue and observe the inflammation of the lungs;to detect the expression of F4/80, CD11B, CD206, and CD86 in mouse lung tissue through flow cytometry to reflect the polarization of macrophages and their M1/M2.

Result: Compared with the uninfected group, macrophages have increased significantly in infected group; The expression of CD206 in macrophages has significantly enhanced after infection, indicating the macrophage polarization towards M2;

Conclusion: MRSA pulmonary infection leads to a significant infiltration of macrophages in lung tissue and their polarization towards the M2 phenotype.