Cancer represents a major worldwide disease burden marked by escalating incidence and mortality. While therapeutic advances persist, developing safer and precisely targeted modalities remains imperative. Nanomedicines emerges as a transformative paradigm leveraging distinctive physicochemical properties to achieve tumor-specific drug delivery, controlled release, and tumor microenvironment modulation. By synergizing passive enhanced permeation and retention effect-driven accumulation and active ligand-mediated targeting, nanoplatforms enhance pharmacokinetics, promote tumor microenvironment enrichment, and improve cellular internalization while mitigating systemic toxicity. Despite revolutionizing cancer therapy through enhanced treatment efficacy and reduced adverse effects, translational challenges persist in manufacturing scalability, longterm biosafety, and cost-efficiency. This review systematically analyzes cutting-edge nanoplatforms, including polymeric, lipidic, biomimetic, albumin-based, peptide engineered, DNA origami, and inorganic nanocarriers, while evaluating their strategic advantages and technical limitations across three therapeutic domains: immunotherapy, chemotherapy, and radiotherapy. By assessing structure-function correlations and clinical translation barriers, this work establishes mechanistic and translational references to advance oncological nanomedicine development.
Humans ; Neoplasms/radiotherapy* ; Immunotherapy/methods* ; Nanoparticles/chemistry* ; Animals ; Nanomedicine/methods* ; Drug Delivery Systems/methods* ; Drug Carriers/chemistry* ; Radiotherapy/methods*

Objective:To investigate the denoising performance of different deep learning (DL) strategies on low-dose brain 18F-FDG PET images. Methods:This retrospective methodological study was conducted on brain PET/CT images of 50 patients (35 males, 15 females, age 20-87 years) who received 3.7MBq/kg 18F-FDG at the Fifth Affiliated Hospital of Sun Yat-sen University between May 2023 and January 2024. Full-dose PET data were acquired with 2min scan. CT scans were acquired before PET scanning. Low-dose PET sinograms were generated by down-sampling the full-dose list mode data to 1/2, 1/4, and 1/20 of full-dose count level. Both full-dose and low-dose sinograms were reconstructed with random, CT-based attenuation and scatter corrections using the three-dimensional (3D) ordered-subsets expectation maximization (OSEM) algorithm (2 iterations, 20 subsets). A total of 4 DL denoising methods were established: (1) 3D conditional generative adversarial networks (GAN) using only low-dose PET as input (GAN-1); (2) 3D attention-based GAN (AttGAN) with low-dose PET input (AttGAN-1); (3) 3D AttGAN with low-dose PET and CT inputs (AttGAN-2); (4) 3D AttGAN with frequency-separation using low-dose PET and CT inputs (AttGAN-FS-2). For AttGAN-FS-2, during the frequency division process, high- and low-frequency components were extracted from the PET reconstructed images via Fourier transform, then inversed Fourier transform, denoised separately, and finally combined to produce the final denoised images. The dataset was separated into training (70%), validation (10%) and testing (20%) sets using simple random sampling without replacement with a fixed random seed. A 5-fold cross-validation scheme was then applied to test all 50 patients. Performance was evaluated against full-dose PET using normalized mean square error (NMSE), structural similarity (SSIM), peak signal-to-noise ratio (PSNR), contrast-to-noise ratio (CNR), SUV mean and SUV max bias of selected brain ROIs. Wilcoxon signed rank test was used to analyze the differences between the denoising methods. Results:AttGAN-FS-2 showed the best performance among all dose levels, with statistical difference as compared by low-dose PET and GAN-1 denoised images for NMSE, SSIM, PSNR, and CNR ( Z values: 2.92-6.15, all P<0.005). NMSE, SSIM quantitative evaluation results (median) of each model at 1/20 dose were: GAN-1: 0.08, 0.87, AttGAN-1: 0.08, 0.88, AttGAN-2: 0.07, 0.89, AttGAN-FS-2: 0.06, 0.91, respectively ( Z values: 3.24-5.77, all P<0.005). Conclusion:The DL-based method combined with multiple strategies AttGAN-FS-2 shows improved denoising performance for low-dose brain PET images.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

Lung cancer has the highest incidence and mortality among malignant tumors in China.Persistent subsolid nodules(SSNs)are closely associated with early-stage lung adenocarcinoma.Artificial intelligence(AI),as an emerging technology,is capable of performing in-depth analysis of large-scale imaging data through autonomous learning and possesses the ability to predict outcomes from new data,demonstrating great potential and application prospects in the assessment of SSNs.AI can not only effectively assist radiologists in diagnosis and treatment,but also improve work efficiency while reducing misdiagnosis and missed diagnosis rates.This review summarizes the recent applications and research progress of AI in the assessment of SSNs,to provide new insights for the diagnosis and treatment of SSNs.

Objective To investigate the risk factors for pneumonia complicating infectious mononucleosis(IM)in adults and construct a nomogram prediction model.Methods A retrospective analysis was conducted on 198 IM patients admitted to the Second Affiliated Hospital of Air Force Medical University from January 2015 to December 2021.Patients were divided into pneumonia group(n=52)and non-pneumonia group(n=146)based on whether pulmonary infection occurred during hospitalization.The baseline data(age,gender,place of onset,etc.),clinical manifestations(maximum body temperature,lymph node enlargement,splenomegaly,etc.),and inflammatory indicators[white blood cell count(WBC),C-reactive protein(CRP),etc.]were compared between the two groups.Kaplan-Meier curves were plotted to analyze the key indicators affecting the hospital stay of IM patients.Multivariate logistic regression was used to analyze the independent risk factors for pneumonia complicating IM in adults and construct a nomogram prediction model based on the identified risk factors.The predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and the consistency of the model was assessed using the calibration curve.The fit of the model was evaluated using the Hosmer-Lemeshow test.Additionally,the sensitivity,specificity,and accuracy of the model were assessed using confusion matrix.Results Compared with non-pneumonia group,the pneumonia group had a significantly higher proportion of patients from rural areas,with body mass index(BMI)≥24 kg/m2,smoking history,hepatomegaly,fever duration of≥7 d,as well as increased total hospitalization costs and average daily hospitalization costs,and prolonged hospital stay(P<0.05).The proportion of patients with a history of antibiotic use was lower in the pneumonia group(P<0.05).Kaplan-Meier survival analysis showed that patients from rural areas,with BMI≥24 kg/m2,smoking history,no prophylactic use of antibiotics,fever duration≥7 d,and hepatomegaly had significantly prolonged hospital stays(P<0.05).Multivariate logistic regression analysis revealed that living in a rural area(OR=4.089,P<0.05),hepatomegaly(OR=4.082,P<0.05),and elevated WBC(OR=1.205,P<0.05)were independent risk factors for pneumonia complicating IM in adults,while the prophylactic use of antibiotics(OR=0.142,P<0.05)was an independent protective factor.The area under the ROC curve of the constructed nomogram prediction model was 0.827(95%CI 0.762-0.892),and the slope of the calibration curve was close to 1,and the Hosmer-Lemeshow test showed χ2=5.299,P=0.725,indicating good consistency and fit of the prediction model.The results of the confusion matrix assessment showed that the sensitivity of the model was 0.669(0.624-0.773),the specificity was 0.827(0.724-0.930),and the accuracy was 0.732(0.665-0.793).Conclusion The nomogram prediction model based on place of onset,hepatomegaly,the prophylactic use of antibiotics and WBC has excellent fit and discrimination,providing an effective quantitative tool for prognosis assessment of IM.

Objective:To study the distribution characteristics of current patients with Kashin-Beck disease (KBD) in Molidawa Daur Autonomous Banner (referred to as Morin Banner), and provide suggestions for service management.Methods:Information of KBD current patients in Morin Banner was collected from January 1, 2018 to June 30, 2024 using the "KBD Current Patient Survey System" provided by the Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention. A descriptive study method was used to analyze the basic information and clinical data of current patients.Results:As of June 30, 2024, a total of 6 223 KBD current patients were reported in Morin Banner, and the patients were distributed in 15 townships (towns). There was a statistically significant difference in the prevalence rate of KBD among different townships (towns, χ 2 = 3 069.01, P < 0.001). The minimum age of the KBD current patients was 27 years old, and the maximum was 98 years old, mainly concentrated in the age range of 45 - 74 years old, accounting for 95.7% (5 954/6 223). There was a significant difference in the prevalence rate of KBD among different age groups (χ 2 = 5 912.76, P < 0.001). The male to female ratio was 1.00∶1.14 (2 910 ∶ 3 313), and there was a statistically significant difference in prevalence rate of KBD between genders(χ 2 = 44.38, P < 0.001). The KBD current patients mainly had a primary school education, married, and farmers, accounting for 59.2% (3 685/6 223), 89.8% (5 590/6 223), 93.2% (5 802/6 223), respectively; and the clinical grading of patients is mainly degree Ⅰ. There was a statistically significant difference in the rate of limb disability among patients with different clinical grades (χ 2 = 64.26, P < 0.001). The rate of limb disability in males was higher than that in females (χ 2 = 10.36, P = 0.001). Conclusions:The KBD current patients in Morin Banner are distributed in various township (town), with middle-aged and elderly famers being the main ones. It is necessary to strengthen monitoring of KBD, and pay attention to personalized treatment and management of KBD current patients.

Objective:To examine the impact of the"outpatient+inpatient"bundled integrated payment reform on the utilization of health services for patients with ordinary tuberculosis,and to evaluate its effectiveness in resource allocation and cost containment.Methods:Based on the Andersen model,clinical and health insurance data from a city in Hebei Province were analyzed.An empirical study was conducted on 5 656 patients using Ordinary Least Squares(OLS)regression and Propensity Score Matching(PSM)to assess outpatient and inpatient service utilization and related costs.Results:Patients in the post-reform group showed a significant increase in outpatient visits and outpatient costs(an average increase of approximately 4.809 visits and 266.368 yuan,respectively,P<0.001),while inpatient visits,inpatient costs,and total medical costs significantly decreased(reductions of approximately 0.302 visits,3 638.647 yuan,and 3 372.279 yuan,respectively,P<0.001).Conclusion:The bundled integrated payment model effectively promotes outpatient service utilization,optimizes inpatient resource allocation,and reduces medical costs.However,the sharp increase in outpatient workload may pose a risk of overutilization.Recommendations:Future initiatives should establish a dynamic monitoring and evaluation system that emphasizes both service quality and clinical outcomes in outpatient and inpatient settings.Furthermore,refining incentive and regulatory mechanisms is essential to ensure that cost control measures do not compromise medical quality and patient safety.

Objective To explore the changes of durability properties of reusable surgical gowns when used in dry and wet conditions.Methods Reusable surgical gowns made of single-layer polyester fiber or 3-layer composite material were selected as test samples,and a Martindale abrasion and pilling tester was used as the basic test platform and modified to form fixtures suitable for the wet state environment.The reusable surgical gowns underwent abrasion experiments in wet and dry conditions to observe the changes in their fiber structure,and were subjected to water penetration resistance and swelling strength tests.Results Visually the reusable surgical gowns had few changes of the microscopic textile fiber structure in dry and wet conditions,and the gowns made of single-layer polyster fiber gained advantages over the outer layers of those of 3-layer composite material in abrasion resistance with the same friction cycles.In dry and wet conditions,the hydrostatic pressure values of the gowns of single-layer polyster fiber gradually decreased with the increase of the degree of abrasion,which were always lower than those of the gowns of 3-layer composite material;the swelling strength of the gowns of single-layer polyster fiber was always greater than that of the gowns of 3-layer composite material,which decreased with the deterioration of the wear more significantly than that of the gowns of 3-layer composite material.Conclusion The reusable surgical gowns made of single-layer polyester fiber or 3-layer composite material have few differences in durability and protective properties at the early stages of ablation in dry and wet conditions.The durability of the gowns decreases as the degree of wear increases,while the trend of the decrease is slowing down until the fabric breaks down and completely loses its barrier effect.[Chinese Medical Equipment Journal,2025,46(6):28-33]

Alzheimer's disease(AD), a neurodegenerative disorder associated with aging, is the most prevalent form of dementia.As the aging population continues to expand, AD presents significant health and caregiving challenges for families and society, making it a pressing international public health concern.In recent years, numerous countries have implemented dementia prevention and treatment strategies that emphasize community-based comprehensive approaches.Currently, the community-based AD prevention and treatment model in China is still in the exploratory phase, with community efforts lacking organization.In alignment with China's action plan for advancing dementia prevention and treatment, and to achieve the strategic objective of "healthy aging, " this consensus is based on the principle of three-level prevention and is tailored to the characteristics of AD disease progression.It aims to develop a comprehensive prevention and treatment strategy for AD that is suitable for communities in China, providing technical guidance and support to establish a scientific basis for formulating community AD prevention and treatment models.

Objective:To develop an air transfer stretcher for severely injured patients,so as to meet the requirements of severely injured patients for rapid transport of aviation medical treatment.Methods:The guide rails of hatch of mainstream civil airliner models were analyzed through investigation.Based on the principles of modularization,integration and intelligence,a highly universal and portable aviation stretcher with the functions of rapid transport and life support was designed and developed.The design of the stretcher was verified through simulation analysis and calculation,as well as tests in laboratory,which should meet the requirements of the standards from China Civil Aviation Regulations(CCAR)-25.Results:The results of simulation analysis and tests of laboratory showed that the aviation transport stretcher,and the strength and stiffness of its structure reached to requirement of CCAR-25 standard,which was suit to the portable aviation evacuation of severely injured patients on civil airliners,and the rapid transfer between air and ground.It has the function of supporting life,and the aviation transport stretcher with high universality and convenience can enhance the safety and rescue capability of aviation evacuation system of medical treatment of aviation.Conclusion:The portable aviation stretcher with high-versatility that was researched and developed by this study can effectively solve the problems of life support,injury monitoring,and emergently rescue and treatment during the transport for severely injured patients,which improve the support ability of air-ground transportation for severely injured patients.