AIM: To investigate the diagnostic and prognostic value of differential expression of Cyclin D1 and p53 in eyelid tumors.METHODS: This retrospective study enrolled patients who underwent surgical resection for eyelid tumors at our hospital between March 2018 and March 2023. Participants were categorized into benign and malignant groups based on tumor characteristics. Clinical data were collected. Genetic data for eyelid tumors were obtained from the GEO database, and differential gene analysis, including volcano plot visualization and KEGG pathway enrichment analysis, was performed using the Sangerbox 3.0 platform. Immunohistochemistry was used to detect the expression levels of Cyclin D1, p53, and BAX in tissue samples. Correlations with clinical features were analyzed using Spearman analysis, and prognostic factors were identified via Logistic regression analysis.RESULTS: This study included 69 patients with eyelid tumors(78 eyes), categorized into a benign group(37 patients, 41 eyes)and a malignant group(32 patients, 37 eyes)based on tumor characteristics. There were significant differences between the two groups in histological subtype, TNM staging, vascular invasion, differentiation status, and local infiltration(all P<0.05). Among benign tumors: pigmented nevi in 11 eyes(27%), hemangiomas in 9 eyes(22%), squamous cell papillomas in 5 eyes(12%), epidermoid cysts in 5 eyes(12%), seborrheic keratoses in 4 eyes(10%), neurofibromas in 3 eyes(7%), and both calcifying epithelioma and xanthelasma in 2 eyes each(5%); among malignant tumors: basal cell carcinoma in 18 eyes(49%), meibomian gland carcinoma in 8 eyes(22%), squamous cell carcinoma in 5 eyes(14%), sebaceous gland carcinoma in 4 eyes(11%), lymphoma and malignant melanoma each in 1 eye(3%). At the follow-up cutoff date of March 2025, the 2-year survival rate in the benign group(95%)was significantly higher than that in the malignant group(78%; P<0.05). Bioinformatics analysis identified 4 103 differentially expressed genes, including Cyclin D1, p53, and BAX, which were predominantly involved in pathways such as the p53 signaling pathway and calcium-related signaling. Spearman analysis revealed that local invasion(rs=0.71, P<0.05)and TNM stage(rs=0.73, P<0.05)correlated with Cyclin D1 expression; local invasion(rs=0.76, P<0.05)and histological subtype(rs=0.65, P<0.05)correlated with p53 expression. Logistic regression results indicated that Cyclin D1, p53, TNM staging, and local invasion were prognostic risk factors. ROC curve analysis demonstrated that the combined detection of these four indicators had the highest predictive value for prognosis(AUC=0.83).CONCLUSION: High expression of cyclin D1 and p53 serves as molecular markers for distinguishing benign from malignant eyelid tumors and assessing prognosis. Combined detection of these markers with TNM staging and local invasion demonstrates high predictive value for prognosis.

Objective To investigate the relationship between symptom burden and nutritional status under Traditional Chinese Medicine (TCM) constitution classification in patients undergoing chemotherapy. Methods Data on the physical constitution, symptom burden, and nutritional status of 640 patients with malignant tumors within the 21st–28th days of chemotherapy treatment were collected and analyzed. Results Symptom burden was found to have a positive correlation with nutritional risk and TCM bias (except for idiosyncrasies), suggesting that constitution bias may be an important internal factor for the aggravation of clinical symptoms and malnutrition in patients with cancer. Conclusion The relationship between symptom burden and nutritional status in chemotherapy under the guidance of TCM constitution can be studied to predict the nutritional status and symptom burden of patients after chemotherapy to guide the symptom and nutritional management of patients with cancer in the chemotherapy stage.

Objective: To analyze the epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang Province from 2019 to 2023, so as to provide the reference for strengthening SFTS prevention and control. Methods: Data on laboratory-confirmed SFTS cases in Zhejiang Province from 2019 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System. Meteorological data, geographic environment and socioeconomic factors during the same period were collected from the fifth-generation European Centre for Medium-Range Weather Forecasts, Geospatial Data Cloud, and Zhejiang Statistical Yearbook, respectively. Descriptive epidemiological methods were used to analyze the epidemiological characteristics of SFTS from 2019 to 2023, and a Bayesian spatio-temporal model was constructed to analyze the influencing factors of SFTS incidence. Results: A total of 578 SFTS cases were reported in Zhejiang Province from 2019 to 2023, with an annual average incidence of 0.23/105. The peak period was from May to July, accounting for 52.60%. There were 309 males and 269 females, with a male-to-female ratio of 1.15∶1. The cases were mainly aged 50-<80 years, farmers, and in rural areas, accounting for 82.53%, 77.34%, and 75.43%, respectively. Taizhou City and Shaoxing City reported more SFTS cases, while Shaoxing City and Zhoushan City had higher annual average incidences of SFTS. The Bayesian spatio-temporal interaction model showed good goodness of fit. The results showed that mean temperature (RR=1.626, 95%CI: 1.111-2.378) and mean wind speed (RR=1.814, 95%CI: 1.321-2.492) were positively correlated with SFTS risk, while altitude (RR=0.432, 95%CI: 0.230-0.829) and population density (RR=0.443, 95%CI: 0.207-0.964) were negatively correlated with SFTS risk. Conclusions SFTS in Zhejiang Province peaks from May to July. Middle-aged and elderly people and farmers are high-risk populations. Taizhou City, Shaoxing City, and Zhoushan City are high-incidence areas. Mean temperature, mean wind speed, altitude, and population density can all affect the risk of SFTS incidence.

Since its emergence in the 1980s, the human immunodeficiency virus (HIV) has caused a global pandemic, posing a severe threat to human life and health as well as social development. Although pre-exposure prophylaxis (PrEP) effectively curbs HIV transmission and antiretroviral therapy (ART) significantly extends the lifespan of patients, vaccines remain a pivotal tool for blocking transmission and ending the pandemic. The high genetic variability of HIV-1, the glycan shield of its envelope glycoproteins, and the long-term persistence of latent reservoirs have repeatedly led to bottlenecks in traditional vaccine strategies. In recent years, mRNA technology has offered a novel approach to addressing these challenges, leveraging advantages such as sequence programmability, short production cycles, native conformational expression of antigens, and self-adjuvant effects. In recent years, mRNA vaccine technology has emerged as a transformative solution to longstanding vaccinology challenges, characterized by its sequence programmability, rapid production cycles, native conformational antigen expression, and intrinsic self-adjuvanting properties. Unlike traditional platforms reliant on pathogen culture or recombinant proteins, mRNA vaccines can be expeditiously designed and updated based solely on viral genomic sequences. Lipid nanoparticle (LNP)-encapsulated mRNA facilitates endogenous antigen expression and presentation, simultaneously eliciting potent humoral and cellular immune responses. Within this landscape, self-amplifying mRNA (saRNA) further extends in vivo antigen expression to enhance the persistence of immune responses. Moreover, the LNP delivery system not only protects mRNA from degradation and mediates endosomal escape but also synergizes with mRNA to optimize immune activation via self-adjuvant effects. Importantly, mRNA platforms circumvent the pre-existing immunity associated with viral vectors and the genomic integration risks of DNA vaccines, positioning them as a cornerstone for global pandemic preparedness. This review systematically delineates recent advances in mRNA technology for HIV-1 vaccine development, focusing on four pivotal research frontiers. First, mRNA innovations building upon the RV144 trial optimize antigens through codon modification and multivalent designs to induce more durable and broad-spectrum immunity. Second, particulate mRNA vaccine strategies, utilizing virus-like particles (VLPs) and ferritin nanoparticles, achieve in situ antigen self-assembly, significantly enhancing B cell activation and reducing infection risks in non-human primate models. Third, germline-targeting mRNA vaccines address the low-affinity barrier of broadly neutralizing antibody (bNAp) precursors, efficiently activating rare precursor B cells and promoting affinity maturation. Fourth, therapeutic mRNA vaccines offer unique advantages for an HIV functional cure; combining immunogens with mRNA-encoded adjuvants potentiates cellular immunity, while LNP-mediated “shock-and-kill” strategies specifically activate latent reservoirs to guide immune clearance. Comparative analyses with traditional platforms reveal that mRNA technology redefines antigen production and presentation, simulating chronic infection through sustained expression and enabling dual-pathway presentation via endogenous synthesis. Furthermore, we explore the mechanistic innovations of mRNA vaccines in inducing bNAps: sustained in vivo production prolongs the activation window for precursor B cells and maintains germinal center (GC) reactions; endogenously expressed antigens adopt native conformations to expose conserved epitopes; and self-adjuvanting effects modulate the functions of antigen-presenting cells (APCs) and follicular helper T cells (Tfh), driving somatic hypermutation and affinity maturation. We also address critical clinical translation challenges, including immune durability, adaptability to special populations, and large-scale LNP manufacturing, while proposing targeted optimization strategies. In conclusion, this review establishes a theoretical framework for utilizing mRNA technology to overcome HIV-1 immune escape, transitioning from a descriptive paradigm to a problem-solving-based synthesis of evidence. By integrating preclinical and early clinical data, we bridge the gap between basic design and translational verification. mRNA technology is poised to become a central pillar inHIV-1 prevention and therapy, providing a robust toolset to achieve the global goal of ending the AIDS pandemic and offering a blueprint for vaccine development against other recalcitrant infectious diseases.

In March 2024, three male and two female specimens of the genus Lispe were intercepted on cargo ships inbound for Wan Zai Port under Gongbei Customs. Based on morphological characteristics and molecular analysis, the specimens were identified as Lispe pumila. In this study, we describe the morphological features, diagnostic characteristics, and geographical distribution of L. pumila, with the aim of providing a reference for the identification of this species when intercepted at ports.

ObjectiveTo develop and preliminarily validate a prediction model for brace treatment failure risk in patients with adolescent idiopathic scoliosis (AIS), based on information obtained before brace treatment and during initial brace fitting. MethodsA total of 191 patients with AIS who initiated thoracolumbosacral orthosis treatment at Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from March, 2015 to August, 2024 and had determinable outcomes were retrospectively included. Patients were divided according to a prespecified scheme into a training set (n = 133) and a validation set (n = 58). Brace treatment failure was defined as progression of the major-curve Cobb angle by ≥ 5° from baseline during follow-up or at brace weaning, or a final major-curve Cobb angle > 45°. Logistic regression, random forest, support vector machine with radial basis function kernel, and extreme gradient boosting (XGBoost) models were developed using routinely available clinical and radiographic variables before brace treatment and during initial brace fitting. Stratified five-fold cross-validation was used for hyperparameter tuning in the training set. Model performance was evaluated in the validation set using the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), Brier score, calibration curves, and decision curve analysis (DCA). SHapley Additive exPlanations (SHAP) was used to interpret the main explanatory model. ResultsIn cross-validation of the training set, both random forest and XGBoost showed good discriminative performance, with cross-validation-AUC values of 0.871 and 0.880, respectively. In the validation set, the AUC values of random forest and XGBoost were 0.888 and 0.899, the AUPRC values were 0.678 and 0.830, and the Brier scores were 0.086 and 0.076, respectively. Random forest was selected as the primary model for interpretation, with a calibration intercept of 0.091 and a calibration slope of 0.995. SHAP analysis indicated that the in-brace correction rate and the major-curve Cobb angle measured in the brace contributed most to the model predictions. ConclusionThe random forest model developed using routinely available pretreatment and initial-fitting variables shows preliminary predictive value for brace treatment failure risk in AIS, and may provide quantitative support for follow-up scheduling, brace-fit reassessment and early adherence-oriented management.

Psoraleae Fructus is derived from the dried fruit of the Psoralea corylifolia L. It has the effects of tonifying the kidney, strengthening the Yang, warming the spleen and stopping diarrhea, and is used for the treatment of kidney deficiency and impotence, lumbar soreness and cold pain, osteoporosis and other diseases, and it is a commonly used tonic traditional Chinese medicine in Chinese medicine clinics in China. However, in recent years, the clinical adverse reactions of Psoraleae Fructus (PF) and related preparations have been increasingly reported, especially hepatotoxicity, which has become a bottleneck in the clinical application of PF and associated preparations. The safety of PF was rarely recorded in ancient texts, but modern clinical and experimental research has shown that PF not only has direct toxicity but also has immune-idiosyncratic toxicity. For this reason, this study comprehensively analyzes the evolution of PF effect/toxicity records in ancient and modern canonical literature, and combines with the progress of modern pharmacology and toxicology research, to conduct an in-depth discussion on the clinical characteristics, causative mechanisms and risk factors of PF hepatotoxicity. On this basis, based on the three-dimensional "human-medicine-use" precise prevention and control strategy for the safety risk of traditional Chinese medicine proposed by the author's team, safety risk prevention and control measures for PF and related preparations were developed, aiming at guiding the safe and rational use of PF and related preparations in the clinic and promoting the healthy and sustainable development of PF-related industries.

Direct compression is an ideal method for tablet preparation, but it requires the powder's high functional properties. The functional properties of the powder during compression directly affect the quality of the tablet. 15 parameters such as Py, FES-8KN, FES-12KN, FES-16KN, CR-8KN, CR-12KN, and CR-16KN were used as the characteristic variables in this paper. Unsupervised learning methods like principal component analysis, cluster analysis, and factor analysis were applied to analyze and classify the compression behavior data of 36 traditional Chinese medicine powders. The results showed that both different dimensionality reduction classification methods could effectively differentiate the compression behavior characteristics of 36 traditional Chinese medicine compound powders. The hierarchical cluster analysis results showed a better agreement with the actual compression phenomena of the powders, where group 1 was high elasticity and low compressibility, group 2 was easily compressed and hard to break, group 3 was excellent compressibility and compactibility. This study is expected to provide references and ideas for predicting the behavior of traditional Chinese medicine powders and the screening of tablet formulations.

Objective: To analyze respiratory syncytial virus(RSV) outbreaks surveillance results and the epidemiological characteristics in kindergarten and school in Shenzhen during 2017-2023 , so as to provide a scientific reference for control and prevention of RSV. Methods: Epidemiological data and surveillance results of RSV outbreaks in kindergarten and school from 2017 to 2023 were collected for descriptive analyses. Results: A total of 31 RSV outbreaks were identified in kindergarten and school in 2017-2023 in Shenzhen, 346 cases were reported, the average incidence rate was 22.02%. The most annual RSV outbreaks were reported in 2020 with 14 outbreaks, followed by 8 outbreaks in 2023. A total of 64.52% of RSV outbreaks were identified in kindergarten with rest occurring in primary school or middle school. The greatest monthly count of outbreak was 18 (58.06%) in September, followed by 3 outbreaks (9.68%) in March and October. A total of 244 swab samples were collected, 169 samples were positive for respiratory viruses, the positive rate was 69.26%, 121 samples were positive for RSV,from 31 respiratory syncytical virus outbreaks 57 and samples were positive for other respiratory viruses(9 samples were positive for two respiratory viruses). A toral of 14(45.16%) outbreaks are caused by RSV alone, 17 outbreaks (54.84%) were caused by RSV and other respiratory viruses. Conclusions Most RSV outbreaks in kindergarten and school are reported after 2020 in Shenzhen, most RSV outbreaks occur in kindergarten, peak seasons of RSV outbreaks are autumn and spring.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.