Compared to other refractive surgeries, the implantable collamer lens(ICL)implantation procedure has become one of the most popular surgical options in refractive surgery. ICL surgery offers advantages such as reversibility, high-definition visual outcomes, and preservation of the corneal anatomical structure. The V4c model, which features a central port, is currently the most widely used in clinical practice and eliminates the need for peripheral iridotomy during the perioperative period. Although excellent uncorrected visual acuity can be achieved postoperatively, some patients may experience visual disturbances in the early postoperative period, such as halo and glare, which may affect visual comfort particularly under low-light conditions. This article reviews visual quality metrics after ICL V4c implantation, including higher-order aberrations(HOA), modulation transfer function(MTF), and contrast sensitivity(CS), along with influencing factors, and discusses potential relative deficits in postoperative visual quality and their underlying mechanisms.

BackgroundIn recent years， the incidence of depression among adolescents has been increasing steadily， posing a serious threat to their physical and mental health and even leading to severe consequences such as self-harm and suicide. At the same time， the detection rate of subclinical depression symptoms among adolescents is even higher. Although these symptoms do not meet the clinical diagnostic criteria， they have significantly affected their quality of life， and their persistence over time may further develop into depression. Therefore， in-depth exploration of adolescent depression symptoms and the predictive factors holds significant practical significance and research value. However， up to now， no large-scale investigation and research on depression symptoms among children and adolescents has been conducted in Inner Mongolia Autonomous Region. ObjectiveTo understand the prevalence of depressive symptoms among children and adolescents in Inner Mongolia Autonomous Region， in order to provide references for formulating scientific and effective prevention strategies and intervention measures. MethodsBy using the cluster stratified random sampling method， 6 281 students from the third grade of primary school to the second grade of high school in 12 leagues and cities of Inner Mongolia Autonomous Region were selected in March 2024. A self-designed questionnaire and the Self-rating Depression Scale （SDS） were used for on-site investigation. ResultsA total of 6 058 （96.45%） children and adolescents completed the valid questionnaire survey， and 2 728 cases （45.03%） were found to have depressive symptoms. There were statistically significant differences in the detection rates of depressive symptoms among children and adolescents of different genders， ages， whether they were only children， different family types， family monthly income， parents' educational levels， and whether the mother was employed （χ²=33.769， 40.618， 48.593， 29.972， 142.648， 195.999， 168.190， 5.445， P<0.05 or 0.01）.The results of the Logistic regression analysis showed that for children and adolescents， being female， aged between 12 and 16， over 16 years old， not being an only child， living in a reconstituted family， having a monthly family income of less than 5 000 yuan， and having parents with an education level of primary school or below were predictors of depressive symptoms （OR=1.241， 1.427， 1.273， 1.177， 1.549， 1.278， 1.462， 1.417， 1.514， 1.929， 1.660， 1.528， P<0.05 or 0.01）. ConclusionThe detection rate of depressive symptoms among children and adolescents in Inner Mongolia Autonomous Region is relatively high. Factors that may predict depressive symptoms in children and adolescents include female gender， ages between 12 and 16， ages over 16 years old， non-only children， families with a restructured structure， monthly family income of less than 5 000 yuan， and parents with an education level of primary school or below. ［Funded by Science and Technology Planning Project of the Inner Mongolia Autonomous Region （number， 2022YFSH0119）］

Background Ozone (O₃) is a major air pollutant. The existing monitoring system has uneven distribution of sites, insufficient coverage in underdeveloped areas, and low temporal resolution, making it difficult to obtain hourly data. This limits the dynamic identification of pollution and the formulation of prevention and control strategies. Objective To construct an hourly O₃ concentration estimation model based on ensemble machine learning, aiming to improve the accuracy of pollution exposure assessment and explore O₃ health impacts. Methods This study integrated land use regression modeling with modern machine learning techniques, employing random forest and XGBoost algorithms to construct base models, and stacking integration using non-negative least squares. The ensemble model was trained and validated across China using high-resolution, multi-source geographic data (e.g., meteorologicaldata, population density, land cover types, and aerosol optical thickness). It was tested in Taiyuan City, combined with a distributed lag non-linear model to analyze the association between O₃ and emergency admissions. Results The constructed ensemble model performed well in predicting O₃ concentration, with a higher coefficient of determination (R²) and a lower root-mean-square deviation (RMSE) compared to the single models. The R² improved from 0.90 to 0.92, and the RMSE decreased from 11.41 to 10.62, enhancing both prediction accuracy and generalization ability. In the application to Taiyuan City, the model successfully imputed the hourly-level data for the entire year. The distributed lag non-linear model analysis revealed that the relative risk (RR) values for the 6th to 8th days following O₃ exposure were 1.14 (95%CI: 1.01, 1.29), 1.16 (95%CI: 1.02, 1.31), and 1.14 (95%CI: 1.01, 1.29), respectively, which were significantly higher than 1, indicating a significant lagged association (lagged 6-8 d) between O₃ and the number of emergency room visits. Conclusion A high-precision, hourly-level O₃ concentration estimation model is successfully constructed by combining the land use regression model with an ensemble machine learning approach to provide a scientific basis for environmental policy formulation and public health intervention. The application of the model verifies its generalization ability and practical application value, which can provide a new technical framework for subsequent environmental health research.

Background Silicosis, an occupational lung disease induced by chronic silica (SiO₂) exposure, is pathologically defined by progressive pulmonary fibrosis, and its associated molecular mechanisms are not yet fully elucidated. Objective To understand the critical role of macrophage-derived vesicles in silicotic pulmonary fibrosis via their carried complement component 1r (C1R). Methods Through integrated analysis of human plasma vesicle proteomics and spatial transcriptomics in silicosis mouse models, the key molecular C1R was identified in silicotic fibrosis. Spatial transcriptomic data were further employed to analyze the expression distribution of C1R in lung tissues. In animal experiments, a mouse silicosis model was established via tracheal instillation of silica dust, followed by pulmonary fibrosis assessed by Sirius Red staining, and C1R expression levels in plasma and lung tissue vesicles examined by Western blot. In cellular experiments, an in vitro model was constructed by stimulating macrophages with silica. Extracellular vesicles isolated from this system were then co-cultured with mouse lung fibroblasts (MLG),followed by intervention with a C1R-neutralizing antibody. Results The proteomic analysis of human plasma vesicles revealed a significant upregulation of C1R in silicosis patients, confirmed by Western blot. The spatial transcriptomics in silicotic mice indicated elevated C1R expression in lung tissues after 56 d of SiO₂ exposure, colocalizing with fibrotic lesions. The results of Western blot further demonstrated increased C1R levels in both lung tissue-derived and peripheral blood-derived vesicles during silicosis progression, consistent with the findings in an ex vivo macrophage model. The results of functional assays demonstrated that macrophage-derived vesicles significantly increased the expression of fibrosis markers, including fibronectin 1 (FN1), collagen type I alpha 1 (COL1A1), and alpha-smooth muscle actin (α-SMA), as well as the migratory capacity of lung fibroblasts; these effects were blocked by the C1R-neutralizing antibody. Conclusion Macrophage vesicles drive fibroblast activation and migration through C1R. Since a C1R-neutralizing antibody blocks this pro-fibrotic effect, C1R represents a key mediator in silicosis and thus is considered a new potential therapeutic target.

OBJECTIVE To improve the inventory turnover rate of traditional Chinese medicine （TCM） decoction pieces in hospitals and achieve refined inventory management for cost reduction and efficiency improvement. METHODS Inventory data of TCM decoction pieces in our hospital from 2022 to 2023 were collected. Based on the sale amount and demand coefficient of variation respectively， the ABC classification method and XYZ analysis method were adopted for classification. The two classification results were combined through a cross matrix to divide them into three-level management priorities： level Ⅰ （AX， AY， BX）， level Ⅱ （AZ， BY， CX）， and level Ⅲ （BZ， CY， CZ）. Differentiated inventory strategies were formulated for each level， and core indicators such as turnover rate and inventory cost before and after inventory management optimization were compared. RESULTS There were 58 types （14.22%） in level Ⅰ， 85 types （20.83%） in level Ⅱ， and 265 types （64.95%） in level Ⅲ. After inventory management optimization， the average inventory value of TCM decoction pieces decreased by 341 800 yuan， the average turnover rate increased by 73.03%， and the average turnover days decreased by 4.98 days. The differences in all indicators before and after optimization were statistically significant （ P ＜0.01）. CONCLUSIONS The ABC-XYZ analysis method can break through the single-dimensional limitation of the traditional ABC classification method， adapt to characteristics such as the strong seasonality of TCM decoction pieces， significantly optimize the inventory structure， improve turnover efficiency， and reduce operating costs. It provides a feasible plan for the refined and scientific management of hospital TCM warehouses.

OBJECTIVE To explore the antidepressant mechanism of Wenyang jieyu granules （WYJYG） via the NOD-like receptor thermal protein domain associated protein 3 （NLRP3）/apoptosis-associated speck-like protein containing a CARD （ASC）/Caspase-1 pathway. METHODS A rat model of depression was established by chronic unpredictable mild stress combined with single-housing for 42 consecutive days.The experiment set up blank group， model group， MCC950 （NLRP3 inflammasome inhibitor） group （10 mg/kg）， fluoxetine group （positive control，2.08 mg/kg），low-dose WYJYG（3.78 g/kg） and high-dose WYJYG group （7.56 g/kg），with 10 rats in each group. From the 22nd day of the experiment， rats in the fluoxetine group， low-dose and high-dose WYJYG groups were intragastrically administered with the corresponding drugs and intraperitoneally injected with an equal volume of normal saline. Rats in the MCC950 group were intraperitoneally injected with MCC950 at the corresponding concentration and intragastrically administered with an equal volume of distilled water. Rats in the blank group and model group were given an equal volume of distilled water by gavage and an equal volume of normal saline by intraperitoneal injection. All interventions were performed once a day for 21 consecutive days. Behavioral tests were conducted once a week. After the last administration， the contents of ASC， ionized calcium binding adaptor molecule 1 （Iba1）， interleukin-1β （IL-1β）， and IL-18 in hippocampal tissues were detected. The protein expressions of NLRP3， cluster of differentiation 68 （CD68）， Caspase-1， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein were determined， and neuronal apoptosis was observed. RESULTS After the last administration， compared with the model group， the open-field activity time was significantly prolonged （ P ＜0.05）， and the latency to feed in a novel environment was significantly shortened （ P ＜0.05） in rats of the high-dose WYJYG group. In hippocampal tissue， the contents of ASC， Iba1， IL-1β， and IL-18， as well as the protein expression levels of NLRP3， Caspase-1， and CD68， and the positive rate of neuronal apoptosis were all significantly decreased/downregulated （ P ＜0.05）. Bcl-2 protein expression was significantly upregulated （ P ＜0.05）， and the density of neuronal apoptosis-positive cells was significantly reduced （ P ＜0.05）. CONCLUSIONS WYJYG play on antidepressant role by inhibiting the NLRP3/ASC/Caspase-1 pathway， reducing microglia-mediated neuroinflammation， and inhibiting hippocampal neurons apoptosis.

ObjectiveTo investigate the value of Fried Frailty Phenotype （FFP）， liver frailty index （LFI）， and Short Physical Performance Battery （SPPB） in predicting 2-year all-cause mortality and decompensation events in patients with liver cirrhosis. MethodsA total of 277 patients with liver cirrhosis who were hospitalized in Beijing Friendship Hospital， Capital Medical University， from December 2020 to December 2021 were enrolled， and FFP， LFI， and SPPB were used to assess the state of frailty. Based on the scores of each tool， these patients were divided into frail and non-frail groups. These three tools were compared in terms of consistency and independent predictive performance. The primary endpoints were 2-year all-cause mortality rate and composite endpoints （death+decompensation events）， and the Cox regression analysis， the receiver operating characteristic （ROC） curve， net reclassification index （NRI）， and integrated discrimination improvement （IDI） index were used to analyze the predictive value of the three tools. Normally distributed continuous data were compared between two groups using the independent samples t-test， while non-normally distributed continuous data were compared using the Mann-Whitney U test. Categorical data were compared between groups using the chi-square test or Fisher’s exact test. The agreement among different frailty tools was evaluated using Cohen’s Kappa statistic. The Kaplan-Meier survival curve was plotted， and a survival analysis was performed using the log-rank test. ResultsThe prevalence rate of frailty assessed by FFP， LFI， and SPPB was 37.2%， 22.4%， and 20.2%， respectively， with a moderate consistency between FFP and LFI/SPPB （κ=0.57， 95% confidence interval ［CI］： 0.47 — 0.67； κ=0.51， 95%CI： 0.41 — 0.62） and a relatively high consistency between LFI and SPPB （κ=0.87， 95%CI： 0.80 — 0.94）. Compared with the non-frailty group， the frailty group had significantly higher all-cause mortality rate and incidence rate of composite endpoints （P0.001）. After multivariate adjustment， FFP， LFI， and SPPB had a hazard ratio of 2.42（95%CI： 1.51 — 5.11）， 2.21（95%CI： 1.11 — 4.42）， and 2.21（95%CI： 1.14 — 4.30）， respectively， in predicting all-cause mortality， as well as a hazard ratio of 2.51（95%CI： 1.61 — 3.91）， 2.40（95%CI： 1.51 — 3.80）， and 2.20（95%CI： 1.39 — 3.47）， respectively， in predicting composite endpoints. Compared with Child-Pugh score， FFP had a significantly greater area under the ROC curve （AUC） in predicting all-cause mortality （0.79 vs 0.69， P=0.032） and composite endpoints （0.75 vs 0.68， P=0.044）. Frailty assessment tools combined with Child-Pugh score significantly improved the performance in predicting all-cause mortality and composite endpoints， with an AUC of 0.81 — 0.82 and 0.77 — 0.78， respectively （P0.05）. NRI and IDI analyses further confirmed the improvement of the combined model in classification （all P0.001）. ConclusionFFP， LFI， and SPPB can independently predict adverse outcomes in patients with liver cirrhosis， among which FFP has the best predictive performance， and the combination of frailty assessment tools with Child-Pugh score can significantly enhance the accuracy of prognostic evaluation.

OBJECTIVE: To observe the effect of acupuncture at "four pharyngeal points" on simple vocal tics with liver hyperactivity disturbed wind in children. METHODS: Sixty children with simple vocal tics of liver hyperactivity disturbed wind were randomly divided into an observation group (30 cases, 1 case dropped out) and a control group (30 cases). The control group was given Changma Xifeng tablets orally, 3 times a day, while the observation group was treated with acupuncture at "four pharyngeal points" on the basis of the treatment in the control group, 15-20 min a time, once daily for 7 days, with a 3-day break. Both groups were treated for 3 months. The TCM syndrome score and Yale global tic severity scale (YGTSS) score of the two groups were observed before treatment and after 1, 2, 3 months of treatment, the disappearance time of simple vocal tics was recorded, and the therapeutic efficacy was evaluated after treatment. RESULTS: After 1, 2, 3 months of treatment, the TCM syndrome scores and YGTSS scores of the two groups were decreased compared with those before treatment (P<0.01, P<0.05), and the scores of the observation group were lower than those in the control group (P<0.05, P<0.01). The disappearance time of simple vocal tics in the observation group was earlier than that in the control group (P<0.05). The effective rate of the observation group was 93.1% (27/29), which was higher than 73.3% (22/30) in the control group (P<0.05). CONCLUSION Acupuncture at "four pharyngeal points" could improve symptoms in children with simple vocal tics of liver hyperactivity disturbed wind, and shorten the disappearance time of simple vocal tics.
Humans ; Male ; Acupuncture Points ; Female ; Child ; Acupuncture Therapy ; Drugs, Chinese Herbal/administration & dosage* ; Child, Preschool ; Liver/drug effects* ; Tics/drug therapy* ; Treatment Outcome