AIM:To investigate the current status and influencing factors of knowledge-attitude-practice in myopia prevention and control among children and adolescents in Ningbo City, thereby providing a scientific basis for formulating targeted prevention strategies.METHODS: Children and adolescents aged 6-12 years old were selected from the medical-school collaborative myopia prevention network in Ningbo City between August 2024 and May 2025 using stratified cluster sampling. Information on myopia prevention knowledge(15 items)and practice(9 items)was collected through questionnaire surveys. Logistic regression models were used to analyze factors influencing myopia occurrence in children and adolescents.RESULTS: A total of 664 children and adolescents aged 6-12 years were enrolled in this study. Participants were divided by age into three groups: 6-7 years old(n=221), 8-9 years old(n=221), and 10-12 years old(n=222). Of the 664 questionnaires distributed, 637 valid questionnaires were returned(201 from the 6-7 age group, 235 from the 8-9 age group, and 201 from the 10-12 age group), yielding an effective response rate of 95.9%. Based on myopia screening results, the non-myopic group comprised 203 participants(31.9%), including 100 males and 103 females, with a mean age of 8.82±1.98 years old. The myopic group comprised 434 participants(68.1%), including 213 males and 221 females, with a mean age of 9.10±1.95 years old. The myopia prevalence rates in the 6-7, 8-9, and 10-12 age groups were 37.8%(76/201), 71.9%(169/235), and 94.0%(189/201), respectively(P<0.001). Regarding the knowledge and practice of myopia prevention, the overall awareness rate in the non-myopic group(59.7%±9.7%)was significantly higher than that in the myopic group(48.7%±8.5%; P<0.001). Additionally, the non-myopic group scored higher on the key practice of “regular eye examinations”(4.27±0.96)compared to the myopic group(4.10±1.05; P<0.05). Logistic regression analysis indicated that age was the primary risk factor for myopia occurrence.CONCLUSION: Age is the dominant factor in the onset of myopia, and there is a phenomenon of “knowledge-practice gap”; the traditional health education model has limitations, and a precise prevention and control system based on developmental patterns should be established.

ObjectiveTo analyze the characteristics of 150 patients with spinal cord injury complicated with spasticity. MethodsA cross-sectional survey was conducted on 150 patients with spinal cord injury accompanied by spasticity from September, 2019 to December, 2024. Their age, gender, cause of injury, injury site, severity of injury, spasticity severity and other indicators were recorded. The relationships between different characteristics were analyzed, and a correlation analysis of disease duration, spasticity grade, injury level, injury severity and age were conducted. ResultsThere was no significant difference in age distribution between patients with tetraplegia and paraplegia (Z = 0.806, P = 0.420). The proportions of trauma (χ² = 3.982, P = 0.046) and tetraplegia (χ² = 10.559, P = 0.010) were higher in males than in females. Trauma was the main cause of injury in both tetraplegia and paraplegia patients; the proportion of tetraplegia was higher than paraplegia in trauma patients, while paraplegia was higher than tetraplegia in non-trauma patients (χ² = 11.885, P < 0.001). Patients with tetraplegia was dominated by incomplete injury, whereas patients with paraplegia was dominated by complete injury (χ² = 10.885, P = 0.012). Grade A injury was predominant in trauma patients (P = 0.003). Spasticity grade showed a very weak positive correlation with disease duration (r = 0.175, P = 0.032) and age (r = 0.168, P = 0.040). Injury severity showed a very weak positive correlation with age (r = 0.183, P = 0.025). ConclusionCharacteristics of patients with spinal cord injury complicated with spasticity is different with gender, cause of injury, injury level, injury severity.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

OBJECTIVE To explore the pharmacokinetic characteristics of 3 blood-absorbed components of Xiangshao sanjie oral liquid in rats with hyperplasia of mammary gland （HMG）. METHODS Female SD rats were divided into control group and HMG group according to body weight， with 6 rats in each group. The HMG group was given estrogen+progesterone to construct HMG model. After modeling， two groups were given 1.485 g/kg of Xiangshao sanjie oral liquid （calculated by crude drug） intragastrically， once a day， for 7 consecutive days. Blood samples were collected before the first administration （0 h）， and at 5， 15， 30 minutes and 1， 2， 4， 8， 12， 24 hours after the last administration， respectively. Using chlorzoxazone as the internal standard， the plasma concentrations of ferulic acid， paeoniflorin and rosmarinic acid in rats were detected by UPLC-Q/TOF-MS. The pharmacokinetic parameters [area under the drug time curve （AUC0－24 h， AUC0－∞）， mean residence time （MRT0－∞）， half-life （t1/2）， peak time （tmax）， peak concentration （cmax）] were calculated by the non-atrioventricular model using Phoenix WinNonlin 8.1 software. RESULTS Compared with the control group， the AUC0－24 h， AUC0－∞ and cmax of ferulic acid in the HMG group were significantly increased （P＜0.05）； the AUC0－24 h， AUC0－∞ ， MRT0－∞ ， t1/2 and cmax of paeoniflorin increased， but there was no significant difference between 2 groups （P＞0.05）； the AUC0－24 h and MRT0-∞ of rosmarinic acid were significantly increased or prolonged （P＜0.05）. C ONCLUSIONS In HMG model rats， the exposure of ferulic acid， paeoniflorin and rosmarinic acid in Xiangshao sanjie oral liquid all increase， and the retention time of rosmarinic acid is significantly prolonged.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.

Head and neck tumors are one of the major diseases that threaten human health. Targeted chemotherapy is an important treatment for head and neck tumors. However, many anti-cancer drugs are difficult to reach effective concentrations in tumors and can cause damage to normal tissues. Therefore, the efficient delivery of anti-tumor drugs, improvement of their therapeutic effects, and reduction of their adverse effects on the whole body and locally are urgent issues in targeted drug research. Liposomes have been widely studied due to their unique characteristics, including amphiphilicity, biocompatibility, biodegradability, and low toxicity. This article outlines the current applications and prospects of liposome drug delivery systems in different treatment modalities for head and neck tumors in recent years, aiming to provide more options for the treatment of head and neck tumors.
Humans ; Liposomes ; Head and Neck Neoplasms/drug therapy* ; Drug Delivery Systems ; Antineoplastic Agents/administration & dosage*

Objective:To explore the features of levels of lung cancer biomarkers in peripheral blood of adults in Beijing and surrounding areas, and establish personalized reference intervals for these biomarkers.Methods:A cross sectional study was conducted. The lung cancer biomarker data, including carcinoembryonic antigen (CEA), cytokeratin 19 fragment antigen 21-1 (CYFRA21-1), neuron specific enolase (NSE), progastrin-releasing peptide (ProGRP), and squamous cell carcinoma antigen (SCC-Ag), collected from adults who underwent cancer prevention examinations at the Cancer Hospital of the Chinese Academy of Medical Sciences from July 2021 to July 2022 were retrospectively analyzed. The interquartile range method was used to eliminate outliers, and the P95 value was calculated. Upper limit of 5 lung cancer biomarkers in different gender and age groups were obtained by referring to the reference intervals of quantitative analytes in the clinical laboratory (WS/T 402-2024). By analyzing the data of 208 adults who underwent cancer prevention physical examinations at the same center in June 2021 and 140 patients with benign lung masses confirmed by surgical resection pathology from January 2016 to June 2022, the established reference intervals for biomarkers were validated. Results:Two thousand six hundred and twenty-six cases of apparently healthy physical examiners were included for constructing reference intervals, including 1 456 males (55.4%) and 1 170 females (44.6%); the age range was 20-88 years old. The serum levels [ M ( Q1, Q3)] of CEA, NSE, ProGRP, SCC-Ag and CYFRA21-1 in 2 626 cases were 1.63 (1.07, 2.43) ng/ml, 13.08 (11.44, 14.77) ng/ml, 34.93 (29.02, 42.19) pg/ml, 0.80 (0.60, 1.00) ng/ml and 1.96 (1.48, 2.63) ng/ml, respectively. The serum levels of CEA [1.88 (1.22, 2.76) ng/ml vs. 1.41 (0.93, 2.02) ng/ml], NSE [13.31 (11.87, 15.00) ng/ml vs. 12.69 (10.96, 14.53) ng/ml], SCC-Ag [0.9 (0.7, 1.1) ng/ml vs. 0.7 (0.6, 0.9) ng/ml], and CYFRA21-1 [2.02 (1.53, 2.71) ng/ml vs. 1.87 (1.40, 2.51) ng/ml] in males were higher than those in females, and ProGRP [34.00 (28.25, 41.55) pg/ml vs. 36.12 (29.97, 42.98) pg/ml] was lower than that in females, and the differences were statistically significant (all P < 0.001). There were statistically significant differences in serum CEA levels between the groups of ≤ 40 years old (458 cases), >40-50 years old (827 cases), >50-60 years old (783 cases), >60-70 years old (412 cases), and >70 years old (146 cases) in pairwise comparison (all P < 0.05). Except for the age groups of ≤ 40 years old and >40-50 years old and the age groups of >60-70 years old and >70 years old, there were statistically significant differences in serum NSE levels among the other age groups in pairwise comparison (all P < 0.05). There were statistically significant differences in serum ProGRP levels between the 5 age groups (all P < 0.05). There were statistically significant differences when comparing the serum SCC-Ag level in the >40-50 age group, >50-60 age group and >60-70 age group with that in the ≤40 age group and >70 age group, respectively (all P < 0.05). However, there was no statistically significant difference between the other age groups in pairwise comparison (all P > 0.05). There were statistically significant differences in serum CYFRA21-1 levels between the 5 age groups (all P < 0.05). When gender and age were not distinguished, the P95 values of serum CEA, NSE, ProGRP, SCC-Ag and CYFRA21-1 levels were 4.44 ng/ml, 16.61 ng/ml, 57.65 pg/ml, 1.50 ng/ml, and 4.21 ng/ml, respectively. Considering gender and age, except for the >70 age group with no statistically significant difference in the P95 value of serum CEA level between males and females ( P > 0.05), the P95 value of serum CEA level in males was higher than that in females in all other age groups (all P < 0.001); the P95 values of serum CEA level in both males and females increased with age, but showed a decreasing trend in males over the age of 70. The P95 value of serum NSE level in males was higher than that in females in the age groups of ≤ 40 years and >40-50 years (both P < 0.05), while there was no statistically significant difference in the P95 value of serum NSE level between males and females in other age groups (all P > 0.05). The P95 values of serum NSE level in both males and females decreased firstly and increased later with age, reaching their highest levels at the age of >70. The P95 values of serum ProGRP level in females aged ≤ 40 and >50-60 were higher than those in males (both P < 0.05), while there was no statistically significant difference in the P95 value of serum ProGRP level between genders in other age groups (all P > 0.05); the P95 values of serum ProGRP level in both males and females increased with age. There was no statistically significant difference in the P95 value of serum SCC-Ag level between males and females in the ≤ 40 age group ( P > 0.05), while the P95 value of serum SCC-Ag level in males was higher than that in females in all other age groups (all P < 0.05). The P95 values of serum SCC-Ag level in males increased with age, while they were stable in females. There was no statistically significant difference in the P95 value of serum CYFRA21-1 level between males and females in the >60-70 age group ( P > 0.05), while the P95 value of serum CYFRA21-1 level in males was higher than those in females in all other age groups (all P < 0.05); the P95 values of serum CYFRA21-1 level in both males and females increased with age. Based on data from 2 626 apparently healthy physical examiners, reference intervals for the levels of 5 lung cancer biomarkers were constructed in different age groups of different genders. Validation was conducted on 208 physical examiners and 140 patients with benign lung lesions, and it was found that the compliance rate of using newly created reference intervals for different gender and age groups to interpret detection results was >90%, and the validation was passed. Conclusions:There are gender and age differences in the reference intervals of CEA, CYFRA21-1, NSE, ProGRP, and SCC-Ag in peripheral blood of adults in Beijing and surrounding areas. The constructed reference intervals of gender and age for biomarkers have been validated and shown good results, providing reference for optimizing the clinical application of lung cancer-related biomarkers.

Objective:To analyze the influencing factors of severe dengue fever patients in the early stage, construct a early prediction model for severe dengue fever, and evaluate it.Methods:A retrospective analysis was conducted to collect early clinical data of dengue fever patients admitted to the People's Hospital of Mengla County and the Third People's Hospital of Kunming in Yunnan Province from July to December 2023. The multifactor logistic regression was used to analyze the factors affecting the severe dengue fever patients, and Nomogram prediction model was used for visualization. Receiver operating characteristic (ROC) curve and calibration curve analysis were used to evaluate the model.Results:A total of 534 dengue fever patients were included, including 291 males and 243 females, aged (39.95 ± 15.69) years. Among them, there were 59 cases (11.05%) of severe dengue fever. The results of multifactor logistic regression analysis showed that age ( OR = 1.05, 95% CI: 1.02 - 1.08, P < 0.001), cardiovascular disease ( OR = 5.28, 95% CI: 2.08 - 13.40, P < 0.001), serous effusion ( OR = 4.34, 95% CI: 1.63 - 11.57, P = 0.003), aspartate aminotransferase ( OR = 1.03, 95% CI: 1.02 - 1.04, P < 0.001), lactate dehydrogenase ( OR = 1.00, 95% CI: 1.00 - 1.01, P = 0.001), and fibrinogen ( OR = 0.46, 95% CI: 0.28 - 0.76, P = 0.003) were independent influencing factors in the early stage of severe dengue fever. The area under the ROC curve of the Nomogram prediction model constructed from the above six variables was 0.96 (0.93 - 0.98). The calibration curve analysis results showed that the mean absolute error between the predicted values of the Nomogram prediction model and the actual observed values was 0.014. Conclusions:Age, cardiovascular disease, serous effusion, aspartate aminotransferase, lactate dehydrogenase, and fibrinogen are independent influencing factors in the early stage of severe dengue fever. The Nomogram prediction model established based on these variables has good predictive ability for severe dengue fever.

Objective:To quantify thoracic and abdominal movements during breathing using inertial measurement units (IMUs) and to build a machine learning model which identifies the abdominal breathing (AB) pattern.Methods:Ten rehabilitation therapists formed the study′s professional group, while 15 patients receiving AB training comprised the validation group. Two synchronized IMUs were applied to capture breathing motions during natural breathing (NB), deep breathing (DB) and AB. Six kinematic features were extracted from each respiratory cycle, and inter-group and inter-pattern differences were analyzed. Correlation analysis was also performed with manually measured changes in thoracic and abdominal circumferences. A support vector classification model for AB pattern detection was then developed using data from the professional and validation groups.Results:A total of 1113 respiratory cycles were extracted and analyzed. The breathing pattern significantly influenced all of the kinematic features studied (0.21≤partial η 2≤0.65, all P≤0.001). The ranges of the angles in medial-lateral axis of the IMUs showed strong correlation with the changes in abdominal and thoracic circumferences (ρ1=0.928, ρ2=0.807, P≤0.001 in both cases). A greater range of abdominal angles was found during AB compared to the other patterns. The best of the models achieved an F1 score of 0.970 (sensitivity: 0.983, specificity: 0.980) in validation. Conclusions:AB generates the greatest abdominal movement. Combining IMUs and machine learning can provide real-time quantification of chest movement and accurate detection of AB during breathing training.

Objective:To investigate the incidence, risk factors, and outcomes of falls among the elderly community population in Beijing.Methods:A cross-sectional survey was conducted using stratified multistage random sampling to select urban and rural residents aged 65 years and older in Beijing. Mortality data was collected after the baseline survey for 5 years. The incidence of falls was weighted based on the composition ratios of age and gender from the 2010 Nation-wide Population Census of Beijing. A logistic regression model was used to analyze the impacts of demographic sociology of common chronic diseases on fall occurrence. The Cox proportional hazards regression model was used to analyze the fall and 5-year survival association.Results:A total of 2 968 participants completed the questionnaire, at cross-sectional survey, with an average age of (73.2±6.0) years, and 1 581 (53.8%) participants were female. Three hundred and sixty-one individuals experienced a fall within the past year. Among those who fell, 64 (17.7%) fell twice, and 95 (26.6%) fell three or more times. Of them, 14.4% (52) had post-fall fractures, with the wrist, knee, and hip being the most common fracture sites, accounting for 25.0%, 17.3%, and 15.4%, respectively. The weighted fall incidence was 12.4% (95% CI: 11.2%-13.5%). Aging, being female, and living in rural areas were more likely to fall. Logistic regression analysis showed that after adjusting for age, gender, and urban-rural status, the risk of falls for those living alone ( OR=1.48, 95% CI: 1.08-2.04) or living with children/grandchildren ( OR=1.51, 95% CI: 1.15-1.97) were significantly higher than those living with their spouse. In addition, the risk of falls was elevated significantly among the elderly with hypertension, diabetes, stroke, dementia, depression status, urinary incontinence, arthritis, insomnia, vision, and hearing loss, dependence on activities of daily living (ADL), general and poor self-rated health (SRH). The Cox proportional hazard regression model revealed that the 5-year risk of death increased by 65% ( HR=1.65, 95% CI: 1.29-2.11) for those who experienced a fall, which increased with fall frequency. This elevated risk persisted after adjusting for chronic conditions, ADL, and SRH. Conclusions:Ageing, female, living in rural regions, having common chronic diseases, dependence on ADL, general and poor SRH, living alone or living with children/grandchildren were associated with the elevated fall risk. The occurrence of fall was seasonal. The most common short-term adverse consequence after a fall was fractures, while the long-term effect was an increased risk of death.