AIM: To explore the efficacy and safety of repeated low-energy red light irradiation combined with visual training for the treatment of adolescent myopia based on vision and tear film function.METHODS: A total of 104 adolescent myopic patients(208 eyes)from the Second Hospital of Hebei Medical University from January 2022 to July 2023 were selected and randomly divided into two groups by random number table method, with 52 cases(104 eyes)in the control group and 52 cases(104 eyes)in the study group. Both groups were treated with orthokeratology lenses, while the control group received visual training and the study group received repeated low-energy red light treatment on top of visual training. Follow-up for 1 a, the improvement of vision, changes in the choroid, tear film function, adverse events, and visual acuity growth after 1 a were compared between the two groups before and after treatment.RESULTS: The uncorrected visual acuity(LogMAR)and axial length of the study group were lower than those of the control group after 6 mo and 1 a of treatment(all P<0.05). The thickness of the choroid under the center recess and the density of choroidal capillary blood flow were higher in the study group than in the control group at 6 mo and 1 a after treatment(all P<0.05); there was no statistically significant difference in the thickness of tear film lipid layer and tear film break-up time between the two groups at different time points(all P>0.05); and the incidence of adverse events during the treatment period of the two groups was not statistically significant(P>0.05). After treatment for 1 a and removing the orthokeratology lens for 2 wk, there was no significant difference in the uncorrected visual acuity(LogMAR)between the study group and the control group before treatment(P>0.05), and the uncorrected visual acuity of the control group was better than that before treatment(P<0.05).CONCLUSION: Repeated low-energy red light combined with visual training can effectively improve the choroid, control the axial length growth, effectively correct the vision of the cornea, and does not affect the tear film function, with high safety.

Acute lung injury (ALI) has been a kind of acute and severe disease that is mainly characterized by systemic uncontrolled inflammatory response to the production of huge amounts of reactive oxygen species (ROS) in the lung tissue. Given the critical role of ROS in ALI, a Fe₃O₄ loaded bovine serum albumin (BSA) nanocluster (BF) was developed to act as a nanomedicine for the treatment of ALI. Combining with NIR irradiation, it exhibited excellent ROS scavenging capacity. Significantly, it also displayed the excellent antioxidant and anti-inflammatory functions for lipopolysaccharides (LPS) induced macrophages (RAW264.7), and Sprague Dawley rats via lowering intracellular ROS levels, reducing inflammatory factors expression levels, inducing macrophage M2 polarization, inhibiting NF-κB signaling pathway, increasing CD4⁺/CD8⁺ T cell ratios, as well as upregulating HSP70 and CD31 expression levels to reprogram redox homeostasis, reduce systemic inflammation, activate immunoregulation, and accelerate lung tissue repair, finally achieving the synergistic enhancement of ALI immunotherapy. It finally provides an effective therapeutic strategy of BF + NIR for the management of inflammation related diseases.

Objective:To investigate the impact of coronary angiography-derived index of microcirculatory resistance (caIMR) on the long-term prognosis of patients with coronary heart disease (CHD) undergoing elective percutaneous coronary intervention (PCI).Methods:The study was a retrospective cohort study conducted at a single centre. Patients who successfully underwent elective PCI with pre-and post-PCI caIMR measurements in Peking University First Hospital between August 2013 and December 2020 were included. Then patients were categorised into three groups based on pre-and post-PCI caIMR: post-PCI caIMR<25 U group, pre-PCI caIMR<25 U and post-PCI caIMR≥25 U group, and both pre-and post-PCI caIMR≥25 U group. Collected clinical data of patients, including comorbid diabetes mellitus.The primary endpoint was a composite endpoint, defined as a composite of all-cause death, non-fatal myocardial infarction, and any revascularisation. The association between caIMR-based groupings and clinical outcomes was analysed using Cox proportional hazards regression models.Results:A total of 625 patients who underwent successful elective PCI were included in the study, among whom 294 (47.0%) had stable angina. The age was (64.5±10.1) years, and 440 (70.4%) patients were male. Over a median follow-up of 3.69 (1.80, 5.80) years, 122 patients (19.5%) experienced composite endpoint events. Post-PCI caIMR≥25 U in combination with diabetes mellitus was associated with an increased risk of the composite endpoint compared to those with post-PCI caIMR<25 U and without diabetes mellitus (adjusted HR=2.13, 95% CI 1.17-3.88, P=0.014). In the combined analysis, compared with post-PCI caIMR<25 U group, those with both pre-and post-PCI caIMR≥25 U had higher risks of composite endpoint (adjusted HR=2.01, 95% CI 1.18-3.43, P=0.010) and any revascularisation (adjusted HR=2.12, 95% CI 1.17-3.84, P=0.013). The pre-PCI caIMR<25 U and post-PCI caIMR≥25 U group showed no statistically significant differences in any of the endpoints compared to post-PCI caIMR<25 U group. Conclusions:Integrated pre-and post-procedural assessment of caIMR may enhance risk stratification in patients with coronary heart disease. Persistent coronary microvascular dysfunction present both before and after PCI, as measured by caIMR, serves as an independent risk factor for adverse events in patients with coronary heart disease undergoing elective PCI.

Objective:To investigate the uptake patterns of 18F-fluorodeoxy glucose ( 18F-FDG) in the endometrium using positron emission tomography (PET) imaging and to differentiate these from stage IA endometrial cancer. Methods:From September 2022 to April 2024, a prospective inclusion of 354 women without gynecological diseases and no hormone usage who underwent 18F-FDG PET-CT examinations at the affiliated hospital of Qingdao University were set as the physiological group, while a group containing 42 cases of Stage IA endometrial carcinoma was also set. The physiological group was divided into five groups based on the menstrual cycle: menstrual period, proliferative phase, ovulatory phase, secretory phase, and menopausal phase. The images were analyzed using visual and quantitative measurements; quantitative analysis indicators were standardized uptake value maximum (SUVmax) and the region of interest/liver ratio (R/L value). Receiver operating characteristic (ROCs) curve was used to determine the optimal cutoff values for SUVmax and R/L value. A clinical model was established using binary logistic regression, and ROC curves were drawn to evaluate the predictive performance of the model. Results:The uptake of 18F-FDG in the endometrium exhibited cyclical variations throughout different physiological phases, with higher uptakes observed during the menstrual and ovulation phases (SUVmax values of 6.66±3.26 and 3.89±1.21, respectively), which are significantly higher than those in the proliferative phase [median SUVmax of 2.54 (2.02, 3.47)], secretory phase (SUVmax of 2.55±0.86), and menopausal phase [SUVmax median of 2.04 (1.69, 2.29)]. During the menstrual and ovulation phases, the radiotracer accumulation patterns were triangular in 105 cases, oval in 32 cases, and round-like in 2 cases. All 42 cases of endometrial cancer showed 18F-FDG uptake, with radiotracer accumulation patterns being round-like in 17 cases, oval in 10 cases, triangular in 9 cases, and irregular in 6 cases. There were statistically significant differences in the shapes of radiotracer concentration between the menstrual, ovulatory periods, and endometrial carcinoma (both P＜0.001). The SUVmax and R/L values in menstrual period and ovulatory period were significantly lower than that in endometrial carcinoma group ( P＜0.001). During the menstrual phase, the optimal cutoff values for SUVmax and R/L in distinguishing between endometrial and endometrial cancer were 12.59 and 3.81, respectively, with corresponding AUCs of 0.885 and 0.842. After incorporating endometrial uptake morphology into the model, the AUCs was improved to 0.969 and 0.948, respectively. During the ovulatory phase, the optimal cutoff values for SUVmax and R/L were 5.96 and 2.85, respectively, with AUCs of 0.984 and 0.968. After integrating endometrial uptake morphology into the model, the AUCs were increased to 0.999 and 0.998, respectively. Conclusions:The 18F-FDG PET imaging of the endometrium shows higher uptake during the menstrual and ovulatory periods, primarily triangular in shape; endometrial carcinoma uptake is significantly higher than the physiological uptake during the menstrual and ovulatory periods, mainly in circular, oval, and irregular shapes. When SUVmax≥5.96, R/L≥2.85, combined with the physiological cycle of the subjects and the morphological characteristics of the radiotracer concentration, it is possible to effectively differentiate between physiological uptake and Stage IA endometrial carcinoma.

Objective:To analyze the influencing factors of knee joint stiffness in patients with tibial plateau fractures after arthroscopy and construct a predictive model.Methods:The clinical data of 154 patients with tibial plateau fractures from June 2020 to May 2023 in Xi'an Daxing Hospital were retrospectively analyzed. All patients were treated with arthroscopic assisted internal fixation surgery. The gender, age, body weight, fracture cause, Schatzker classification, osteoporosis, meniscus and ligament structure injury, lower limb malalignment, bone graft, knee extension device injury, internal fixation method, external fixation time, heterotopic ossification, Tscherne classification, drainage tube placement, debridement times, operation opportunity and anesthesia method were recorded. The patients were followed up for 1 year, and the occurrence of knee joint stiffness was recorded. The patients were divided into knee joint stiffness group and normal knee joint group. Multivariate Logistic regression was used to analyze the independent risk factors of knee joint stiffness after arthroscopy in patients with tibial plateau fractures. R language software package was used to construct the nomogram model for predicting the knee joint stiffness after arthroscopy in patients with tibial plateau fractures, calibration curve was drawn, and the Bootstrap method was used to verify the model discrimination. The predictive value of model was evaluated by the receiver operating characteristics (ROC) curve.Results:Among 154 patients with tibial plateau fractures, 28 patients developed knee joint stiffness after arthroscopy (knee joint stiffness group), with an incidence rate of 18.18%; 126 patients had normal knee joints (normal knee joint group). The proportions of obesity, meniscus and ligament structure injury, knee extension device injury, lower limb malalignment and heterotopic ossification in knee joint stiffness group were significantly higher than those in normal knee joint group, and there were statistical differences ( P<0.05 or <0.01); there were no statistical differences in gender composition, age, fracture cause, osteoporosis, Schatzker classification, bone graft, internal fixation method, external fixation time, Tscherne classification, drainage tube placement, debridement times, operation opportunity and anesthesia method between the two groups ( P>0.05). Multivariate Logistic regression analysis result showed that obesity, meniscus and ligament structure injury, knee extension device injury, lower limb malalignment and heterotopic ossification were independent risk factors for knee joint stiffness after arthroscopy in patients with tibial plateau fractures ( OR = 5.387, 4.613, 3.308, 3.178 and 4.579; 95% CI 1.207 to 24.034, 1.447 to 14.709, 1.063 to 10.291, 1.155 to 8.745 and 1.540 to 13.613; P<0.05 or <0.01). The body weight, meniscus and ligament structure injury, knee extension device injury, lower limb malalignment and heterotopic ossification were used as predictors to construct a nomogram model for predicting the knee joint stiffness after arthroscopy in patients with tibial plateau fractures. The calibration curve analysis result showed that the theoretical curve was basically consistent with the actual curve trend trajectory ( C- index = 0.861). The ROC curve analysis result showed that the model for predicting the knee joint stiffness after arthroscopy in patients with tibial plateau fractures had good accuracy (area under curve was 0.861), with the sensitivity of 92.9% and specificity of 73.0%. Conclusions:The patients with tibial plateau fractures have the risk of knee joint stiffness after arthroscopy, which may be related to patient obesity, meniscus and ligament structure injury, knee extension device injury, lower limb malalignment and heterotopic ossification. Based on these risk factors, a column chart risk prediction model can be constructed to visualize the risk and have certain predictive value for knee joint stiffness within 1 year after surgery.

OBJECTIVE To establish a population pharmacokinetic(PopPK)model to predict the PK characteristics of GLS-010 in humans.METHODS Fifty-eight cynomolgus monkeys were used,18 of which were randomly divided into three groups and received a single intravenous infusion of GLS-010 at doses of 2,6,and 18 mg·kg-1,respectively.The rest were randomly assigned to four groups and received multiple intravenous infusions of GLS-010 at doses of 0,5,25,and 100 mg·kg-1,respectively,once a week(quaque week,qw)for five consecutive weeks.Blood samples were collected before and after administration.The concentrations of GLS-010 in the monkey serum were measured using a validated enzyme-linked immunosorbent assay,while those of anti-drug antibodies(ADA)in the cynomolgus monkey serum were determined by ultra-sensitive electrochemiluminescence immunoassay.The PK data on GLS-010 in cynomolgus monkeys was obtained,and the drug-time curves were plotted.A PopPK model was constructed using non-compartmental analysis and evaluated by goodness-of-fit plots and visual predictive checks.The constructed PopPK model was used to predict the PK characteristics in humans,which were finally compared with actual Phase Ⅰ clinical study results for validation.RESULTS The predictive results of the PopPK model were highly consistent with the actual Phase Ⅰ clinical study results.The model was able to predict the human PK characteristics under various dosing regimens,including 1 mg·kg-1 quaque 2 weeks(q2w),4 mg·kg-1(q2w),240 mg(q2w),240 mg(q3w),and 10 mg·kg-1(q2w).The predicted maximum plasma concentrations(Cmax)were 24.8,99.1,85.0,85.0,and 247.8 mg·L-1,respectively,and the AUC0-336h was 4 902.0,20 060.0,17 147.7,22 145.7(AUC0-504h),and 50 817.6 mg·h·L-1,respectively.The safety risks for the corresponding dosing regimens were 47.3,11.6,13.5,10.5,and 4.6,respectively.The predicted receptor occupancy at steady state(ROss)at Cmax,average plasma concentration(Cavg),and minimum plasma concentration(Cmin)were 38.8％,72.7％,69.4％,64.1％and 87.2％,29.1％,63.8％,60.0％,49.8％and 82.1％,21.9％,55.5％,51.3％,36.3％and 76.7％,respectively.CONCLUSION The PopPK model can effectively predict the human PK characteristics under different dosing regimens with high consistency with actual Phase Ⅰ clinical study results,which can serve as an important reference for selection of safe and effective doses for first-in-human research.

Objective To construct a Nomogram prediction model for prognosis of retinopathy of prematurity(ROP)based on serological markers and to validate the predictive value of the model.Methods A total of 195 ROP pa-tients(390 eyes)admitted to the Second Hospital of Hebei Medical University from January 2022 to January 2024 were se-lected.After 3-month follow-up post-treatment,the patients were divided into poor-prognosis(n=41)and good-prognosis(n=154)groups.General data and pre-treatment serological markers[vascular endothelial growth factor(VEGF),insu-lin-like growth factor-1(IGF-1),glutamate(Glu),signal transduction and transcriptional activator 3(STAT3),hypoxic in-ducible factor 3α(HIF-3α)]were compared between the two groups.LASSO-Logistic regression was used to identify risk factors for poor prognosis in ROP patients.A Nomogram prediction model for poor prognosis in ROP patients was construc-ted based on these factors.The predictive value of the model was validated using receiver operating characteristic(ROC)curves,calibration curves,and decision-curve analysis.Results The 1-min Apgar score,5-min Apgar score,proportion of severe disease,proportion of bronchopulmonary dysplasia(BPD),proportion of sepsis,and pre-treatment serum levels of VEGF,Glu,STAT3,and HIF-3α were higher in the poor-prognosis group than in the good-prognosis group,while gesta-tional age,birth weight,and serum IGF-1 levels were lower(all P＜0.05).LASSO-Logistic regression analysis showed that gestational age,disease severity,BPD,sepsis,and pre-treatment serum levels of VEGF,IGF-1,Glu,STAT3,and HIF-3αwere risk factors for poor prognosis in ROP patients(all P＜0.05).A Nomogram prediction model for poor prognosis in ROP patients was constructed based on these factors.The model had an area under the curve(AUC)of 0.943(95％CI:0.907-0.978)for predicting poor prognosis,indicating high predictive efficacy.The model had good calibration,with good con-sistency between predicted and actual results,and demonstrated good clinical utility in predicting poor prognosis in ROP patients.Conclusion Serum levels of VEGF,IGF-1,Glu,STAT3,and HIF-3α are all prognostic factors for ROP pa-tients.The Nomogram prediction model for ROP prognosis based on these serological markers has high application value.

Objective:To investigate the occurrence and characteristics of adverse reactions of Xuesaitong preparations, mine its coagulation disorders/bleeding risk signals, and provide references for its safe and rational use in clinic. Methods:The reports of adverse drug reactions (ADR) caused by Xuesaitong preparations from August 2003 to August 2023 in the database of Shandong Provincial Center of Adverse Drug Reaction Monitoring were collected. ADR were counted and classified using the system organ class (SOC) and preferred term (PT) of Medical Dictionary for Regulatory Activities 26.1. Three methods, namely the reporting odds ratio (ROR), the proportional reporting ratio (PRR), and the comprehensive standard method of the Medicines and Healthcare Products Regulatory Agency (MHRA) of the United Kingdom, were used to detect the risk signals of coagulation disorders/bleeding in using Xuesaitong preparations. Results:A total of 17 015 reports of ADR related to Xuesaitong preparations were collected, involving 9 dosage forms, in which injection dosage form accounted for 95.50% (16 250/17 015). The median age of the patients was 62 years, 44.87% of the cases were 45-64 years and 42.90% of them were 65 years and above. There were 2 217 cases of severe ADR reports, accounting for 13.03% (2 217/17 015). A total of 18 SOCs were involved, the top 3 were skin and subcutaneous tissue diseases, systemic diseases and drug administration site reactions, and neurological diseases. A total of 54 PTs were not recorded in the instructions, among which 34 were severe. Ninety-three cases about coagulation disorders/bleeding (98 times) were reported, the top 3 PTs were hematuria [24.49% (24/98)], purpura [11.22% (11/98)], and epistaxis [10.20% (10/98)]. Seven dosage forms of Xuesaitong preparations were involved, the top 3 were Xuesaitong for injection (freeze-dried) (48 cases, accounting for 51.61%), Xuesaitong injection (29 cases, accounting for 31.18%), and Xuesaitong tablets (8 cases, accounting for 8.60%). Among 93 reports of coagulation disorders/bleeding, there were 23 severe cases, accounting for 24.73%, which was significantly higher than that in other reports (12.97%), and the difference was statistically significant ( P<0.001). Sixteen PTs about coagulation disorders/bleeding were not recorded in the instructions, among which 9 were severe. The proportion of cases with onset time longer than 7 days in ADRs about coagulation disorders/bleeding was higher than that in other ADRs [22.58%(21/93) vs. 7.43%(1 258/16 922), P<0.001]. The risk signals of coagulation disorders/bleeding were mined for Xuesaitong for injection (freeze-dried), Xuesaitong injection, Xuesaitong tablets, and Xuesaitong capsules, and the risk signal density of Xuesaitong tablets was the strongest. Conclusions:The ADRs of Xuesaitong preparations involve multiple systems and organs. Among them, Xuesaitong for injection (freeze-dried), Xuesaitong injection, Xuesaitong tablets, and Xuesaitong capsules have a strong association with coagulation disorders/bleeding risks, and the proportion of severe cases is relatively high. However, the relevant risk warning information is not included in the drug instructions of some manufacturers. Medication monitoring needs to be strengthened and timely intervention should be carried out in clinic.

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

OBJECTIVE To establish a population pharmacokinetic(PopPK)model to predict the PK characteristics of GLS-010 in humans.METHODS Fifty-eight cynomolgus monkeys were used,18 of which were randomly divided into three groups and received a single intravenous infusion of GLS-010 at doses of 2,6,and 18 mg·kg-1,respectively.The rest were randomly assigned to four groups and received multiple intravenous infusions of GLS-010 at doses of 0,5,25,and 100 mg·kg-1,respectively,once a week(quaque week,qw)for five consecutive weeks.Blood samples were collected before and after administration.The concentrations of GLS-010 in the monkey serum were measured using a validated enzyme-linked immunosorbent assay,while those of anti-drug antibodies(ADA)in the cynomolgus monkey serum were determined by ultra-sensitive electrochemiluminescence immunoassay.The PK data on GLS-010 in cynomolgus monkeys was obtained,and the drug-time curves were plotted.A PopPK model was constructed using non-compartmental analysis and evaluated by goodness-of-fit plots and visual predictive checks.The constructed PopPK model was used to predict the PK characteristics in humans,which were finally compared with actual Phase Ⅰ clinical study results for validation.RESULTS The predictive results of the PopPK model were highly consistent with the actual Phase Ⅰ clinical study results.The model was able to predict the human PK characteristics under various dosing regimens,including 1 mg·kg-1 quaque 2 weeks(q2w),4 mg·kg-1(q2w),240 mg(q2w),240 mg(q3w),and 10 mg·kg-1(q2w).The predicted maximum plasma concentrations(Cmax)were 24.8,99.1,85.0,85.0,and 247.8 mg·L-1,respectively,and the AUC0-336h was 4 902.0,20 060.0,17 147.7,22 145.7(AUC0-504h),and 50 817.6 mg·h·L-1,respectively.The safety risks for the corresponding dosing regimens were 47.3,11.6,13.5,10.5,and 4.6,respectively.The predicted receptor occupancy at steady state(ROss)at Cmax,average plasma concentration(Cavg),and minimum plasma concentration(Cmin)were 38.8％,72.7％,69.4％,64.1％and 87.2％,29.1％,63.8％,60.0％,49.8％and 82.1％,21.9％,55.5％,51.3％,36.3％and 76.7％,respectively.CONCLUSION The PopPK model can effectively predict the human PK characteristics under different dosing regimens with high consistency with actual Phase Ⅰ clinical study results,which can serve as an important reference for selection of safe and effective doses for first-in-human research.