Objective:To investigate the rates of low disease activity and clinical remission in patients with systemic lupus erythematosus(SLE)in a real-world setting,and to analyze the related factors of low disease activity and clinical remission.Methods:One thousand patients with SLE were enrolled from 11 teaching hospitals.Demographic,clinical and laboratory data,as well as treatment regimes were collec-ted by self-completed questionnaire.The rates of low disease activity and remission were calculated based on the lupus low disease activity state(LLDAS)and definitions of remission in SLE(DORIS).Charac-teristics of patients with LLDAS and DORIS were analyzed.Multivariate Logistic regression analysis was used to evaluate the related factors of LLDAS and DORIS remission.Results:20.7％of patients met the criteria of LLDAS,while 10.4％of patients achieved remission defined by DORIS.Patients who met LLDAS or DORIS remission had significantly higher proportion of patients with high income and longer disease duration,compared with non-remission group.Moreover,the rates of anemia,creatinine eleva-tion,increased erythrocyte sedimentation rate(ESR)and hypoalbuminemia was significantly lower in the LLDAS or DORIS group than in the non-remission group.Patients who received hydroxychloroquine for more than 12 months or immunosuppressant therapy for no less than 6 months earned higher rates of LLDAS and DORIS remission.The results of Logistic regression analysis showed that increased ESR,positive anti-dsDNA antibodies,low level of complement(C3 and C4),proteinuria,low household in-come were negatively related with LLDAS and DORIS remission.However,hydroxychloroquine usage for longer than 12 months were positively related with LLDAS and DORIS remission.Conclusion:LLDAS and DORIS remission of SLE patients remain to be improved.Treatment-to-target strategy and standar-dized application of hydroxychloroquine and immunosuppressants in SLE are recommended.

Objective To investigate the molecular mechanism of ulinastatin in reducing lung injury in neonatal sepsis rats.Methods Sepsis-induced lung injury patients(sepsis lung injury group)and healthy newborns born during the same period(control group)were selected as research subjects,and venous blood from newborns of each group was collected for use.Newborn SD rats were randomly divided into blank control group(given an equal volume of 0.9％NaCl),model group(4 mg·kg-1 lipopolysaccharide),and ulinastatin group(4 mg·kg-1 lipopolysaccharide+5 × 104 U·kg-1 ulinastatin),with 12 rats in each group.Survival of the rats within 24 hours of injection was observed,and after 24 hours,blood was collected from the heart,and lung tissues were collected.Real-time fluorescent quantitative polymerase chain reaction was used to detect the expression of CRNDE and miR-29a in serum and lung tissue.Enzyme-linked immunosorbent assay was used to detect the expression of inflammatory factors such as interleukin 6(IL-6).Dual-luciferase reporter gene assay was used to verify the interaction between CRNDE and miR-29a.Kit methods were used to detect reactive oxygen species(ROS)and other oxidative stress indicators.Western blotting was used to detect the expression of heme oxygenase 1(HO-1).In situ fluorescence hybridization was used to detect the expression of CRNDE and miR-29a.Results The serum CRNDE expression levels in control group and sepsis lung injury group were 1.00±0.16 and 0.41±0.09,respectively;the expression levels of miR-29a were 1.00±0.14 and 1.83±0.25,respectively;IL-6 levels were(4.13±0.86)and(12.61±2.57)ng·mL-1,respectively.Compared with the control group,the above indexes in the sepsis lung injury group were statistically significant(all P＜0.05).The lung injury scores of blank control group,model group and ulinastatin group were 0.62±0.24,4.96±1.28,2.13±0.86,respectively;ROS levels were(0.93±0.15),(2.61±0.35),(1.58±0.23)U·mg-1,respectively;the protein levels of HO-1 were 1.00±0.17,2.19±0.31,1.17±0.16,respectively;IL-6 levels were(46.15±7.62),(186.77±21.30),(113.46±14.68)pg·mL-1,respectively;the expression levels of CRNDE were 1.00±0.12,0.41±0.06,0.82±0.13,respectively;the expression levels of miR-29a were 1.00±0.14,2.38±0.21 and 1.62±0.19,respectively.The above indexes were compared between blank control group and sepsis lung injury group,model group and blank control group,ulinastatin group and model group,and the differences were statistically significant(all P＜0.05).Conclusion Ulinastatin may alleviate lung injury in neonatal sepsis through IncRNA CRNDE/miR-29a signaling pathway.

Pharmacokinetics of traditional Chinese medicine(TCM)is a discipline that adopts pharmacokinetic research methods and techniques under the guidance of TCM theories to elucidate the dynamic changes in the absorption,distribution,metabolism and excretion of active ingredients,active sites,single-flavour Chinese medicinal and compounded formulas of TCM in vivo.However,the sources and components of TCM are complex,and the pharmacodynamic substances and mechanisms of action of the majority of TCM are not yet clear,so the pharmacokinetic study of TCM is later than that of chemical medicines,and is far more complex than that of chemical medicines,and its development also confronts with challenges.The pharmacokinetic study of TCM originated in the 1950s and has experienced more than 70 years of development from the initial in vivo study of a single active ingredient,to the pharmacokinetic and pharmacodynamic study of active ingredients,to the pharmacokinetic study of compound and multi-component of Chinese medicine.In recent years,with the help of advanced extraction,separation and analysis technologies,gene-editing animals and cell models,multi-omics technologies,protein purification and structure analysis technologies,and artificial intelligence,etc.,the pharmacokinetics of TCM has been substantially applied in revealing and elucidating the pharmacodynamic substances and mechanisms of action of Chinese medicines,research and development of new drugs of TCM,scientific and technological upgrading of large varieties of Chinese patent medicines,as well as guiding the rational use of medicines in clinics.Pharmacokinetic studies of TCM have made remarkable breakthroughs and significant development in theory,methodology,technology and application.In this paper,the history of the development of pharmacokinetics of TCM and the progress of cutting-edge research was reviewed,with the aim of providing ideas and references for the pharmacokinetics of TCM and related research.

Objective To develop a matrix metalloproteinase(MMP)-responsive hyaluronic acid(HA)-based controlled-release material for brain-derived neurotrophic factor(BDNF)to provide a novel therapeutic strategy for intervention and repair of traumatic brain injury(TBI).Methods HA was modified with amination,followed by condensation with Suflo-SMCC carboxyl group to form amide,and then linked with glutathione(GSH)to synthesize HA-GSH.The recombinant glutathione S-transferase(GST)-tissue inhibitor of metalloproteinase(TIMP)-BDNF(GST-TIMP-BDNF)expression plasmid was constructed using molecular cloning technique with double enzyme digestion by Bam H Ⅰ and Eco R Ⅰ.The recombinant GST-TIMP-BDNF protein was expressed in the Escherichia coli prokaryotic expression system,and purified by ion exchange chromatography,confirmed by Western blotting.MMP diluents were supplemented with PBS,MMP inhibitor marimastat,and varing concentrations(0.4,0.6,0.8 mg/ml)of GST-TIMP-BDNF or GST-BDNF.MMP-2 activity was analyzed using an MMP activity detection kit to evaluate the inhibitory effect of the recombinant protein on MMP.Primary rat neurons were extracted and cultured to establish an iron death model induced by RSL3.The effect of recombinant protein GST-TIMP-BDNF on neuronal injury was detected by immunofluorescence staining.Results MRI hydrogen spectrum identification confirmed the successful synthesis of HA-GSH.Western blotting results showed the successful expression of the recombinant protein GST-TIMP-BDNF containing the GST tag using the E.coli prokaryotic expression system.MMP activity detection results indicated that the recombinant protein GST-TIMP-BDNF had a superior inhibitory effect on MMP-2 activity compared to GST-BDNF(P<0.05).Immunofluorescence staining results showed a significant increase in fluorescence intensity in rat neurons treated with GST-TIMP-BDNF after RSL3 induction(P<0.05).Conclusion A MMP-responsive HA-based BDNF controlled-release material has been successfully developed,exhibiting a protective effect on neuron damage.

A new alkaloid (1) and six known compounds (2-7) were isolated from the solid fermentation extract of the endophytic fungus Alternaria tenuissima Pas85 of Phragmites australis by silica gel column chromatography, Sephadex LH-20 column chromatography, high performance liquid chromatography and other chromatographic techniques. The structures of these compounds were determined by HREIMS, NMR, IR spectroscopy, and literature comparison, and the anti MRSA (methicillin-resistant Staphylococcus aureus) activity of 1-5 were tested. Compounds 1, 2, 3 and 4 exhibited certain inhibitory activity with MIC values of 64, 4, 32 and 32 μg·mL^-1, respectively, and compound 5 showed no significant inhibitory activity.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective To explore medium and long term efficacy of oblique lateral interbody fusion(OLIF)in treating lumbar specific infection.Methods From October 2017 to January 2021,24 patients with lumbar specific infection were treated by OLIF combined with vertebral screw internal fixation,including 15 males and 9 females,aged from 27 to 61 years old with an average of(43.0±15.0)years old;the courses of disease ranged from 6 to 24 months with an average of(14.0±7.0)months;7 patients with L2-L3,12 patients with L3-L4 and 5 patients with L4-L5;19 patients with tuberculosis infection and 5 patients with brucella infection.The amount of intraoperative blood loss,operative time and complications were recorded,and erythro-cyte sedimentation rate(ESR),C-reactive protein(CRP),visual analogue scale(VAS),Japanese Orthopaedic Association(JOA)score and American Spinal Injury Association(ASIA)rating were compared before and one month after opertaion.Re-sults All patients were followed up from 9 to 24 months with an average of(13.0±6.0)months.Operative time was(132.5±21.4)min,and intraoperative blood loss was(227.3±43.1)ml.ESR and CRP were decreased from(82.34±18.62)mmol·h-1 and(53.08±21.84)mg·L-1 before operation to(33.52±17.31)mmol·h-1 and(15.48±8.36)mg·L-1 at one month after opera-tion,respectively(P＜0.05).VAS was decreased from(7.52±1.36)before opertaion to(1.74±0.87)at one month after opera-tion(P＜0.05).JOA was increased from(17.86±3.95)before operation to(24.72±3.19)at one month after operation(P＜0.05).Four patients had neurological symptoms before operation,and were classified to grade D according to ASIA classifica-tion,who were recovered to grade E at 1 month after operation.One patient was suffered from psoas major muscle injury after operation,and returned to normal at 3 weeks.One patient was suffered from abdominal distension and difficulty in defecation,and relieved after gastrointestinal decompression and enema.No complications such as abdominal organ injury and poor wound healing occurred in all patients.Conclusion OLIF combined with vertebral screw internal fixation is a new minimally invasive surgical method for the treatment of lumbar specific infection,especially the lesion located on the middle lumbar vertebra.It has advantages of less trauma,short operation time,less blood loss,convenient operation,complete removal of the lesion,safety and effectiveness,and has good medium-and long-term efficacy for lumbar specific infection.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.