Objective: To analyze the epidemiological characteristics of varicella among nursery children in Shenzhen from 2015 to 2024, and to evaluate the impact of optimizing varicella vaccine (VarV) immunization strategies on varicella incidence. Methods: Varicella incidence data for nursery children in Shenzhen from 2015 to 2024 were obtained from the China Disease Prevention and Control Information System. The study period was divided into three phases:one dose self pay VarV (January 2015 to October 2017), two dose self pay VarV (November 2017 to October 2019), and two dose free VarV (November 2019 to December 2024). Interrupted time series (ITS) analysis was conducted to assess changes in the level and trend of varicella incidence associated with each phase of policy implementation. Results: A total of 27 517 varicella cases was reported among nursery children from 2015 to 2024, with an average annual incidence of 514.01/100 000. During the same period, 136 clustered outbreaks were reported in nursery institutions, involving a cumulative total of 1 091 cases. ITS analysis showed that during the self pay 1 dose stage, the varicella incidence among nursery children showed an upward trend, with an average monthly increase of 2.58/100 000 (95% CI =2.21/ 100 000 -2.95/100 000, P <0.01). After the implementation of the self pay 2 dose strategy, the incidence decreased, with a change in incidence of -26.12/100 000 (95% CI =-37.30/100 000 to -14.94/100 000) and a change in slope of -2.65/100 000 (95% CI = -3.38/100 000 to -1.93/100 000)(all P <0.01). After the implementation of the free 2 dose strategy, the incidence decreased further, with a change in incidence of -40.03/100 000 (95% CI =-50.39/100 000 to -29.66/100 000, P <0.01) and a change in slope of -0.56/100 000 (95% CI =-1.20/100 000-0.08/100 000, P =0.09). Conclusion The gradual optimization of the VarV vaccination strategy in Shenzhen from self pay 1 dose to free 2 dose has significantly reduced the varicella incidence among nursery children, demonstrating good short term control and long term intervention effectiveness.

Pathologic myopia(PM)is characterized by progressive axial elongation, posterior staphyloma, and fundus degenerative changes, representing a leading cause of blindness in Asian countries.Posterior scleral reinforcement(PSR)is currently the only surgical intervention to slow axial elongation. Its mechanisms involve mechanical reinforcement, improved blood circulation, and biological stimulation of scleral remodeling. This article reviews recent advances in PSR: surgical techniques have evolved from complex, classic procedures to standardized single-strip methods, incorporating 3D MRI to quantify posterior staphyloma morphology for personalized graft design and facilitating minimally invasive, precision surgery. Among implant materials, biomaterials such as allogeneic dura mater are being continuously optimized, while biomimetic piezoelectric smart materials actively promote scleral collagen synthesis through electrical signals, achieving a paradigm shift from “passive support”to “active reinforcement”. Clinical outcomes indicate advantages in regulating axial length, enhancing visual function and blood circulation, and facilitating early intervention in children. Combined procedures with ICL implantation, cataract surgery or vitrectomy provide comprehensive treatment regimens for individual patients with varied conditions. This article also analyzes long-term issues and core controversies including ectopic posterior staphyloma and reoperation, and prospects future research directions such as artificial intelligence assistance, translation of smart materials and full-cycle prevention and treatment systems, so as to provide references for clinical practice and scientific research.

Objective: To investigate the current status of hyperopic reserve among preschool children and to determine the associations with genetic and behavioral factors, so as to provide evidence for early intervention strategies and the development of working protocols for myopia prevention with a forward shift of the prevention threshold. Methods: A total of 924 preschool children (3-6 years of age) from 6 kindergartens in Jiading District of Shanghai were enrolled by stratified random sampling from March to June 2024. Cycloplegic refraction using 1% atropine eye drops was performed to obtain accurate spherical equivalent (SE) values. Questionnaires were used to collect the genetic history and daily behavioral habits of the children. Refractive status was classified into three categories based on the SE:sufficient hyperopic reserve, relatively insufficient hyperopic reserve, and pre myopia. Results: The overall detection rate of insufficient hyperopic reserve among preschool children was 82.25%, consisting of 72.29% for relatively insufficient hyperopic reserve and 9.96% for pre myopia. Multivariate Logistic regression analysis showed that parental bilateral myopia was independently and positively associated with relatively insufficient hyperopic reserve ( OR =2.13) and pre myopia ( OR =4.35) compared to children with sufficient hyperopic reserve; electronic screen exposure time ≥2 h/d on school days was an independent and positive risk factor for pre myopia ( OR =2.83); all of the above associations were statistically significant (all P <0.05). No statistically significant association was noted between outdoor activity and hyperopic reserve (all P >0.05). Conclusions The insufficient hyperopic reserve detection rate is relatively high among preschool children in Jiading District, Shanghai. Early management of electronic device use with regular screening and monitoring for preschool children with a family history of myopia should be strengthened to shift the prevention threshold earlier and prevent childhood myopia.

Lung cancer is the leading cause of cancer-related deaths worldwide. While modern medical therapies such as surgery， chemotherapy， and radiotherapy have achieved progress， they often come with severe side effects and drug resistance. Traditional Chinese medicine （TCM）， characterized by its multi-component， multi-target， and holistic regulatory properties， plays a significant role in the adjunctive treatment of lung cancer. It offers unique advantages in alleviating clinical symptoms， enhancing patients' quality of life， prolonging survival， and enhancing efficacy while reducing toxicity， serving as an important therapeutic modality for lung cancer. The theory of cancer-toxin pathogenesis proposes that phlegm-toxin is a key pathogenic factor in lung cancer， with phlegm-toxin mutual entanglement being the core pathogenesis of lung cancer. The pathogenic characteristics-viscosity， dispersion， and damage to the healthy Qi-of phlegm-toxin are closely related to the accumulation of acidic metabolic products， tumor invasion and metastasis， and immune suppression during the course of lung cancer. Phlegm resolving and toxin clearing are the core therapeutic methods for lung cancer. Such prescriptions possess dual functions of resolving phlegm and dissipating mass， as well as inhibiting tumor and detoxifying. They exert antitumor effects through multiple pathways， including regulating metabolic reprogramming of glucose and lipids， improving the acidic microenvironment of tumors， and inhibiting inflammatory signaling pathways. This paper systematically reviews the current clinical application status and mechanisms of phlegm-resolving and detoxifying Chinese herbal medicines. By integrating the theory of cancer-toxin pathogenesis with modern pharmacological research findings， this paper explores their application in lung cancer treatment and establishes a clinical application system for phlegm-resolving and detoxifying therapies in lung cancer based on phlegm-toxin pathogenesis. This system integrates ancient and modern experiences with contemporary mechanisms， aiming to provide theoretical foundations and practical references for integrated traditional and Western medicine diagnosis， treatment， and drug development for lung cancer and other conditions.

Objective To estimate the biological dose in a patient who developed radiation dermatitis after a local X-ray exposure incident. Methods Peripheral blood samples, which were used to performed lymphocyte chromosome aberration analysis, were collected from the patient at 54 and 102 days after the last exposure. Biological dose in the patient was estimated using four published X-ray dose-effect calibration curves for chromosomal aberrations. The absorbed dose in the patient was reconstructed using Dolphin′s model and time correction factors. Results The abnormal rates of chromosome aberration at 54 and 102 days after exposure were 1.00% and 0.40%, respectively. Based on the four calibration curves, the estimated local exposure dose at 54 day ranged from 3.59 to 10.51 Gy, and the time-corrected whole-body equivalent dose ranged from 0.27 to 0.87 Gy. The local dose estimated at 102 days ranged from 2.24 to 6.64 Gy, with a time-corrected whole-body equivalent dose of 0.12 to 0.60 Gy, which differed from the day-54 estimates. The biological doses estimated by both methods were lower than the physical dose (29.43 Gy). Conclusion The estimation of local biological dose of patient various in four dose-effect curves selected in this study. Delayed blood sampling will lead to underestimate biological dose. Early blood collection after radiation incidents is critical to ensure accuracy and reliability. Moreover, biological dose reconstruction methods for complex exposure scenarios require further research to improve the accracy of emergency response in radiation accidents.

Objective To explore the feasibility of applying artificial intelligence (AI) technology in chromosomal aberration (CA) analysis for occupational health surveillance of radiation workers and in biological dose estimation during nuclear emergency responses. Methods Peripheral blood samples from healthy volunteers were irradiated in vitro with X-rays and cobalt-60 (⁶⁰Co) γ rays. Chromosome slides were prepared using an automated harvesting and dropping device. The data training and outcome evaluation of CA analysis was performed on the AI software using chromosome images from occupational medical examination of radiation workers from the current lab or chromosome slides from blood samples irradiated with X-rays. The trained AI software was then used to assist in CA analysis and biological dose estimation among occupational medical examination of radiation workers, with results compared with manual reading and actual exposure doses. Results The trained AI software achieved a CA recognition accuracy of 95.11%. In the occupational health examination of radiation workers, the positive CA detection rate using AI + manual review was 2.25% higher than that in manual reviewing alone. The errors in biological dose estimation for ⁶⁰Co γ rays and X-rays using AI + manual review analysis were 11.86% and 7.33%, respectively, both within the acceptable 20.00% error margin. Conclusion AI + manual review can be effectively applied in CA analysis for occupational health examination and biological dose estimation during nuclear emergencies, significantly improving analysis efficiency.

Objective:To analyze the spatiotemporal correlation between the surveillance data of influenza in students reported by medical institutions and school absenteeism due to illness, and evaluate the application of Bayesian Structural Time Series model (BSTS) in the prediction of school influenza epidemic.Methods:A total of 13 schools in Dapeng new district of Shenzhen were selected. The incidence data of influenza in schools in Shenzhen from January 1, 2015 to December 31, 2019 were collected from China Disease Control and Prevention Information System and the illness related school absentence data during this period were collected from Shenzhen Student Health Surveillance System, and the spatiotemporal correlation between the data from two systems was analyzed and compared. BSTS was used to make long-term predictions of the monthly incidence of influenza in students in 2019 and short-term predictions of the weekly incidence of influenza in week 1-8 and week 45-52 of 2019 by using the data from two systems.Results:There was a temporal correlation between the data from China Disease Control and Prevention Information System and the data from Shenzhen Student Health Surveillance System ( r=0.93, P<0.001), and the lag of the former one was 1 day ( r=0.73, P<0.001). Influenza outbreaks were randomly distributed in different schools in Shenzhen, and there was no spatial correlation. The root mean square error ( RMSE) and mean absolute error ( MAE) were 0.35 and 0.28, respectively, in the long-term prediction, and the RMSE was 0.33 and 0.34, and the MAE was 0.26 and 0.28, respectively, in the short-term predictions of week 1-8 and week 45-52 of 2019, respectively, showing good prediction accuracy and fitting effect. Conclusion:By analyzing the data from China Disease Control and Prevention Information System and Shenzhen Student Health Surveillance System with BSTS, the dynamics of the school influenza epidemic can be accurately predicted, and effective technical support can be provided for the early warning and prevention and control of influenza epidemic.

Objective:To analyze the temporal distribution of other infectious diarrhea (OID) in Shenzhen and provide evidence for the prevention and control of OID.Methods:The incidence data of OID in Shenzhen from 2011 to 2023 were collected. The seasonal and trend decomposition using loess (STL), seasonal index method, concentration degree and circular distribution method were used to analyze the incidence trend and temporal distribution of OID.Results:A total of 477 611 cases of OID were reported in Shenzhen from 2011 to 2023, with an average annual incidence rate of 260.19/100 000 showing a fluctuating upward trend. The seasonal index method indicated that October-January was period with high incidence of OID in Shenzhen and the seasonal intensity began to decrease in 2020. STL revealed an obvious incidence peak in winter. The concentration method showed that OID had a certain seasonality before 2018 except 2016, but the seasonality was not obvious after 2018. The circular distribution results showed that r was 0.05, mean angle ā was 1.92° and angular standard deviation s was 141.93° ( Z=1 033.37, P<0.001), with the peak on January 1 st and the high incidence period from August 11 th to May 25 th. Conclusions:OID had a certain degree of seasonality in Shenzhen, with an obvious incidence peak in winter. Since the seasonal intensity of OID decreased after 2018, the surveillance, early warning and risk assessment of OID should be continued, and prevention and control measures should be adjusted timely according to the change in the characteristics of the epidemic.

Objectives:To analyze the epidemiological characteristics and incidence trends of chronic hepatitis B in Shenzhen from 2005 to 2023, develop a prediction models with performance evaluation, explore its associations with social demographic index (SDI) and inform targeted prevention strategy development.Methods:Based on surveillance data of infectious diseases, descriptive epidemiological methods were applied to analyze the spatiotemporal and population distribution characteristics. A multifactorial prediction model integrating the SDI was established, and its predictive performance was evaluated by using data from 2020-2023. Model accuracy was evaluated by using root mean square error and mean absolute percentage error ( MAPE). The association between SDI and incidence rates was assessed through generalized linear models. Results:A total of 235 703 chronic hepatitis B cases were reported cumulatively in Shenzhen from 2005-2023, with an annual average incidence rate of 98.84/100 000. Long-term trends revealed a significant increase in the incidence from 2005 to 2019. The incidence rate was 2.48 times higher in men than in women, and the majority of cases occurred in age group 20-50 years. The cases were mainly workers in manufacturing and services. Seasonal incidence peaks were observed in March and during May to November. The overall SDI exhibited a consistent upward trend, and the positive correlation between SDI and incidence rate was observed in central urban districts (Futian and Nanshan). In contrast, industrial zones (Guangming and Bao'an) saw a significant decline in incidence rates due to intensified prevention interventions despite the increase of SDI level. Model predictions indicated that the multivariate long short-term memory (LSTM) deep learning model integrating SDI parameters outperformed both the spatiotemporal covariate- enhanced model and the augmented Bayesian structural time series model, with MAPE of 4.71%, 7.66% and 10.30%, respectively. Conclusion:SDI is a key social determinant associated with hepatitis B transmission risks, and dynamic thresholds can be established to develop tiered early warning mechanisms. It is suggested to integrate multisource SDI data into the LSTM framework, implement targeted interventions such as "rapid antibody screening in key areas + vaccination boosters for high-risk populations" and improve the timeliness of epidemic response through hybrid models to reduce disease burden level.

Objective:Primary pulmonary mucoepidermoid carcinoma(PMEC)is a rare malignant lung tumor that accounts for approxim-ately 0.1%-0.2%of all primary pulmonary neoplasms.Due to the non-specific clinical symptoms and epidemiological features,PMEC poses diagnostic challenges.Methods:Tissue blocks from 23 archived PMECs were collected from The First Affiliated Hospital of Soochow Uni-versity(November 2012 to December 2023).To establish definitive diagnoses,comprehensive histopathological evaluation,including histo-morphological analysis,immunohistochemistry(IHC),fluorescence in situ hybridization(FISH),and periodic acid-Schiff(PAS)staining were performed.Results:The tumors consisted of varying proportions of mucin-secreting cells(mucous cells),intermediate cells,and epidermoid cells.Immunophenotypically,CK7 was predominantly expressed in the mucous cells,whereas CK5/6,p40,and p63 were expressed in the epidermoid and intermediate cells.The Ki-67 proliferation index ranged from 5%to 60%.All tumors were negative for TTF-1 and Napsin A.Five of the tumors were positive for PD-L1(clone 22C3),with a tumor percentage score of 3%-20%.All 11 tumors tested for ALK(clone D5F3)were negative.IHC for c-Met was performed on two tumors and both were weakly positive(+).Mastermind-like transcriptional co-activator 2(MAML2)gene rearrangement was detected in 34.8%(8/23)of the tumors.Mucous cells were PAS positive.Kaplan-Meier surviv-al analysis revealed a significantly poorer prognosis for patients with lymph node metastasis,distant metastasis,advanced TNM stage(Ⅲ+Ⅳ),poor differentiation,or MAML2 gene rearrangement negativity.Univariate analysis identified poor histological differentiation,lymph node metastasis,distant metastasis,and advanced TNM stage as the major prognostic risk factors.Multivariate analysis confirmed poor differentiation and distant metastasis as independent risk factors for adverse outcomes.Conclusions:PMEC is an aggressive tumor with low incidence and non-specific clinical manifestations,leading to frequent misdiagnosis.Clinicians should maintain a high index of suspicion and ensure a thorough differential diagnosis.