This study aims to determine the therapeutic effect and then elucidate the molecular mechanism of Dietary Yangrong Decoction(DYRT)on blood deficiency syndrome based on net-work pharmacology and study its active compounds.The molecular mechanism of DYRT in the treatment of blood deficiency syndrome was predicted by network pharmacology.The blood defi-ciency of rats was established using cyclophosphamide and acetophenohydrazine jointly,which was divided into a blank control group,a model group,a Men's Yangrong Decoction group(MYRT)(positive control group),a medicinal group and food-based Yangrong Decoction group.The active components were analyzed by liquid chromatography-mass spectrometry(HPLC-MS),the periph-eral hemogram was detected by an automatic biochemical analyzer,the levels of hematopoietic regulatory factors in serum were determined by ELISA,and the relative expression of EPO in kid-ney and PI3K,AKT,GM-CSF in bone marrow were measured by RT-PCR.The results showed that DYRT had 57 active ingredients and 128 potential targets for the treatment of spleen deficien-cy syndrome.1 835 items were obtained by GO enrichment analysis,and 20 pathways were ob-tained by KEGG enrichment analysis;DYRT and MYRT were identified by HPLC-MS to contain 12 same blood active compounds.Animal experiments showed that,compared with the model group,the number of red blood cells,the number of platelets and the content of hemoglobin in the DYRT group were significantly increased,and the number of white blood cells was significantly decreased(P＜0.05).The contents of EPO,IL-3,IL-6 and GM-CSF in serum were significantly in-creased,and the content of TNF-α was significantly decreased(P＜0.05).The relative expression levels of EPO in kidney and PI3K,AKT and GM-CSF mRNA in bone marrow were significantly increased(P＜0.05).Compared with the MYRT group,the number of white blood cells in the DYRT group was significantly reduced,the content of GM-CSF in serum was significantly in-creased,and the content of EPO and GM-CSF mRNA was significantly increased(P＜0.05).In conclusion,DYRT contains the same active compounds as MYRT,which can regulate hematopoi-etic factors,thereby activating the PI3K/AKT pathway to restore hematopoietic function and im-prove the blood deficiency state of the body.

Porcine reproductive and respiratory syndrome virus(PRRSV)mainly causes sow abor-tion,stillbirth,mummified fetus and respiratory symptoms in piglets.Since first reported in China in 1996,the virus complexity has increased significantly in more than 20 years of genetic evolution,bringing huge economic losses to the pig industry.In recent years,with the emergence of various PRRSV recombinant virus strains,preventing and controlling this epidemic became increasingly difficult.The purpose of this article is to comprehensively review the genome structure and func-tion of PRRSV,RNA virus recombination mechanism,main types of recombination,and the epi-demic status and recombination for the dominant epidemic PRRSV strains,in order to provide clues for in-depth research on gene recombination of PRRSV,thus providing the theoretical sup-port for formulating scientific prevention and control strategies.

Objective:To analyze the burden and trends of noncommunicable chronic disease(NCD) attributable to metabolic factors in China from 1990 to 2021.Methods:Data from the Global Burden of Diseases(GBD) 2021 database were utilized to describe changes in mortality and disability-adjusted life years(DALYs) of NCD in China from 1990 to 2021. Stratified analyses were conducted by age, sex, sociodemographic index(SDI), and related risk factors. Statistical analyses and predictions were conducted using the age-period-cohort model and the Nordpred model.Results:In 2021, the age-standardized mortality rate and age-standardized DALYs rate of NCD attributable to metabolic factors in China were 227.56 per 100 000 and 4 829.39 per 100 000, respectively. Their average annual percentage changes were -0.76%( P<0.001) and -0.77%( P<0.001). Overall, the burden decreased progressively with higher SDI levels. Analysis using the age-period-cohort model indicated reduced birth cohort and period effects for metabolic factor-attributable NCD, while age effects rose significantly. The minimum relative risk( RR) value was observed in the 15-19 age group( RR=0.01), and the maximum RR value occurred in the 95-99 age group( RR=996.86). The overall rising mortality trend indicated that age effects are the predominant driver at present. Projections estimate that by 2046, deaths from metabolic factor-attributable NCD in China will reach 8 189 563, with an age-standardized mortality rate of 236.95 per 100 000. Conclusions:China continues to face a substantial burden of NCD linked to metabolic factors, with older adults, males, and individuals with hypertension, diabetes, and prediabetes identified as key populations requiring targeted interventions.

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 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 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 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.

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.

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.