In this study, potential quality markers(Q-markers) of Schisandrae Chinensis Fructus for treating bronchial asthma were predicted based on analytic hierarchy process(AHP), entropy weight method(EWM), fingerprint, and network pharmacology. AHPEWM was employed to quantitatively identify the Q-markers of Schisandrae Chinensis Fructus. AHP was used to weight the primary indicators(effectiveness, measurability, and specificity), while EWM was employed to analyze the secondary indicators of each primer indicator. Further, through fingerprint combined with network pharmacology, a ″component-target-pathway″ network was constructed to screen the components of Schisandrae Chinensis Fructus for treating bronchial asthma. It was finally determined that schisandrol A,schisandrin A, and schisandrin B were potential Q-markers of Schisandrae Chinensis Fructus in the treatment of bronchial asthma. This study is the first to comprehensively use AHP-EWM, fingerprint, and network pharmacology to screen the key Q-markers of Schisandrae Chinensis Fructus in the treatment of bronchial asthma. This study provides a scientific basis for improving the quality standard of Schisandrae Chinensis Fructus and lays a foundation for studying its material basis in treating bronchial asthma.
Schisandra/chemistry* ; Asthma/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Network Pharmacology ; Humans ; Entropy ; Lignans/analysis* ; Fruit/chemistry* ; Quality Control ; Cyclooctanes ; Polycyclic Compounds/analysis*

AIM To establish a UPLC-ESI-MS/MS method for analyzing the toxic material basis of 95％ethanol cold soaked ultrasonic extract(EC),95％ethanol heated reflux extract(EH)and water decoction extract(WD)from Dryopteris crassirhizoma Nakai.METHODS The analysis was performed on a 25 ℃ thermostatic agilent ZORBAX RRHD StableBond C18 column(2.1 mm×150 mm,1.8 μm),with the mobile phase comprising of methanol-0.2％formic acid flowing at 0.30 mL/min,and heated electrospray ion source was adopted in positive and negative ion scanning.Compounds were identified by Compound Discover 3.3 software combined with the database and related literature,and the main differential components were screened by Heatmap cluster analysis and partial least squares discriminant analysis.RESULTS 72 compounds were identified(22 phloroglucinols,19 flavonoids,8 phenylpropanoids,6 terpenoids and 17 other components).The main toxic differential components were phloroglucinols such as flavaspidic acid AB,didemethylpseudoaspidin AA and filixic acid PBP,flavonoids such as(-)-epicatechin,(-)-epigallocatechin,cianidanol,and other compounds such as indole-3-carboxaldehyde.CONCLUSION This method can rapidly,effectively and comprehensively characterize the main chemical composition of D.crassirhizoma,and provide a reference for the study of its pharmacological mechanism.

OBJECTIVE: To explore the co-morbid influencing factors of postmenopausal osteoporosis(PMOP) and dyslipidemia, and to provide evidence-based basis for clinical co-morbidity management. METHODS: Based on the 2017 to 2018 Beijing community cross-sectional survey data, PMOP patients were included and divided into the dyslipidemia group and the uncomplicated dyslipidemia group according to whether they were comorbid with dyslipidemia. Demographic characteristics, living habits and disease history were collected through questionnaires, and bone mineral density and bone metabolism biomarkers (osteocalcin, blood calcium, serum typeⅠprocollagen N-terminal prepeptide, etc.) were detected on site. Co-morbidity risk factors were analyzed using binary logistic regression. RESULTS: Three hundred and twenty patients with PMOP were included, including the comorbid group (75 patients) and the uncomplicated group (245 patients). The results showed that history of cardiovascular disease [OR=1.801, 95%CI(1.003, 3.236), P=0.049], history of cerebrovascular disease [OR=2.923, 95%CI(1.460, 5.854), P=0.002], frying and cooking methods[OR=5.388, 95%CI(1.632, 17.793), P=0.006], OST results[OR=0.910, 95%CI(0.843, 0.983), P=0.016], and blood Ca results [OR=60.249, 95%CI(1.862, 1 949.926), P=0.021] were the influencing factors of PMOP complicated with dyslipidemia. CONCLUSION Focus should be placed on the influencing factors of PMOP and dyslipidemia co-morbidities, with emphasis on multidimensional assessment, combining lifestyle interventions with bone metabolism marker monitoring to optimize co-morbidity management.
Humans ; Dyslipidemias/epidemiology* ; Female ; Middle Aged ; Osteoporosis, Postmenopausal/metabolism* ; Aged ; Cross-Sectional Studies ; Risk Factors ; Bone Density

OBJECTIVE: To investigate the effect of miR-483-5p on hepatocellular carcinoma (HCC) cells proliferation and stemness, as well as the attenuating effect of Pien Tze Huang (PZH). METHODS: Differentially expressed miRNA between HepG2 cells and hepatic cancer stem-like cells (HCSCs) were identified by a miRNA microarray assay. miR-483-5p mimics were transfected into HepG2 cells to explore the effects of miR-483-5p on cell proliferation and stemness. HepG2 cells and HCSCs were treated with PZH (0, 0.25, 0.50 and 0.75 mg/mL) to explore the effects of PZH on the proliferation and stemness, both in non-induced state and the state induced by miR-483-5p mimics. RESULTS: miR-483-5p was significantly up-regulated in HCSCs and its overexpression increased cell proliferation and stemness in HepG2 cells (P<0.05). PZH not only significantly inhibited proliferation in HepG2 cells, but also significantly suppressed the cell proliferation and self-renewal of HCSCs (P<0.05). The effects of miR-483-5p mimics on proliferation and stemness of HepG2 cells were partially abolished by PZH. CONCLUSIONS miR-483-5p promotes proliferation and enhances stemness of HepG2 cells, which were attenuated by PZH, demonstrating that miR-483-5p is a potential molecular target for the treatment of HCC and provide experimental evidence to support clinical use of PZH for patients with HCC.
Humans ; MicroRNAs/metabolism* ; Cell Proliferation/drug effects* ; Liver Neoplasms/drug therapy* ; Carcinoma, Hepatocellular/drug therapy* ; Hep G2 Cells ; Neoplastic Stem Cells/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Gene Expression Regulation, Neoplastic/drug effects*

Peptide-based radiopharmaceuticals targeting integrin α5β1 show promise for precise tumor diagnosis and treatment. However, current peptide-based radioligands that target α5β1 demonstrate inadequate in vivo performance owing to limited tumor retention. The use of PEGylation to enhance the tumor retention of radiopharmaceuticals by prolonging blood circulation time poses a risk of increased blood toxicity. Therefore, a PEGylation strategy that boosts tumor retention while minimizing blood circulation time is urgently needed. Here, we developed a PEGylation-enabled peptide multidisplay platform (PEGibody) for PR_b, an α5β1 targeting peptide. PEGibody generation involved PEGylation and self-assembly. [⁶⁴Cu]QM-2303 PEGibodies displayed spherical nanoparticles ranging from 100 to 200 nm in diameter. Compared with non-PEGylated radioligands, [⁶⁴Cu]QM-2303 demonstrated enhanced tumor retention time due to increased binding affinity and stability. Importantly, the biodistribution analysis confirmed rapid clearance of [⁶⁴Cu]QM-2303 from the bloodstream. Administration of a single dose of [¹⁷⁷Lu]QM-2303 led to robust antitumor efficacy. Furthermore, [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 exhibited low hematological and organ toxicity in both healthy and tumor-bearing mice. Therefore, this study presents a PEGibody-based radiotheranostic approach that enhances tumor retention time and provides long-lasting antitumor effects without prolonging blood circulation lifetime. The PEGibody-based radiopharmaceutical [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 shows great potential for positron emission tomography imaging-guided targeted radionuclide therapy for α5β1-overexpressing tumors.

AIM To establish a UPLC-ESI-MS/MS method for analyzing the toxic material basis of 95％ethanol cold soaked ultrasonic extract(EC),95％ethanol heated reflux extract(EH)and water decoction extract(WD)from Dryopteris crassirhizoma Nakai.METHODS The analysis was performed on a 25 ℃ thermostatic agilent ZORBAX RRHD StableBond C18 column(2.1 mm×150 mm,1.8 μm),with the mobile phase comprising of methanol-0.2％formic acid flowing at 0.30 mL/min,and heated electrospray ion source was adopted in positive and negative ion scanning.Compounds were identified by Compound Discover 3.3 software combined with the database and related literature,and the main differential components were screened by Heatmap cluster analysis and partial least squares discriminant analysis.RESULTS 72 compounds were identified(22 phloroglucinols,19 flavonoids,8 phenylpropanoids,6 terpenoids and 17 other components).The main toxic differential components were phloroglucinols such as flavaspidic acid AB,didemethylpseudoaspidin AA and filixic acid PBP,flavonoids such as(-)-epicatechin,(-)-epigallocatechin,cianidanol,and other compounds such as indole-3-carboxaldehyde.CONCLUSION This method can rapidly,effectively and comprehensively characterize the main chemical composition of D.crassirhizoma,and provide a reference for the study of its pharmacological mechanism.

Objective:To explore the prognostic value of serum free light chain in chronic lymphocytic leukemia patients.Methods:Retrospective cohort study was conducted. One hundred and fifty-six newly diagnosed chronic lymphocytic leukemia(CLL) patients in the first affiliated hospital of Nanjing Medical University from January 2016 to December 2020 were included in the retrospective analysis. Among them, there were 106 males and 50 females, with a median age of 60.7 (53.4, 66.0) years old.Serum sample was collected, serum free light chains were detected, and patients were divided into a treatment group (106 cases) and a follow-up group (50 cases) based on the presence of treatment indications.The threshold of serum free light chain(sFLC) was defined by the reference range of the instruction manual and ROC curve. Three indicators were used, including sFLCR, sFLC(κ+λ) and sFLC(κ-λ). Patients were divided into normal sFLCR group ( n=61)and abnormal group( n=95), as well as sFLC (κ+λ) low value group ( n=88) and high value group ( n=68), and sFLC (κ-λ) low value group ( n=64) and high value group ( n=92).The abnormal group and high value group were enrolled as the experimental group, while the normal group and low value group were enrolled as control group. Chi-square test and Fisher′s exact test were used to compare the clinical data, cytogenetics, and molecular biology characteristics of patients in two groups, Kaplan-Meier method was used to analyze the median treatment-free survival (TFS) of the patients, and Cox regression was used to screen the prognostic factors of the patients. Results:The proportion of Rai stage Ⅰ-Ⅳ ( χ2=8.16, P<0.05 and χ2=7.63, P<0.05 and χ2=5.45, P<0.05), Binet stage B-C( χ2=4.11, P<0.05 and χ2=9.43, P<0.05 and χ2=7.34, P<0.05), β 2-microglobulin>3.5 mg/L( χ2=5.13, P<0.05 and χ2=18.3, P<0.05 and χ2=12, P<0.05), ATM gene mutation rate( χ2=6.21, P<0.05 and χ2=4.88, P<0.05 and χ2=5.19, P<0.05), and immunoglobulin heavy chain variable region (IGHV) mutation free rate ( χ2=18.9, P<0.05 and χ2=24.6, P<0.05 and χ2=10.4, P<0.05)in the experimental group were significantly higher than that in control group 1 ( P<0.05). Multivariate analysis indicated that sFLC(κ+λ) ( HR=1.615,95% CI 1.012-2.576, P=0.044), β 2-microglobulin>3.5 mg/L( HR=2.103,95% CI 1.356-3.262, P=0.001) and TP53 deletion and/or mutation( HR=1.892,95% CI 1.082-3.308, P=0.025) were independent prognostic factors affecting the patients time to first treatment(TFT). Conclusions:Serum free light chains can predict the risk of early treatment and have good prognostic significance in newly diagnosed CLL patients.

Objective:To explore the prognostic value of serum free light chain in chronic lymphocytic leukemia patients.Methods:Retrospective cohort study was conducted. One hundred and fifty-six newly diagnosed chronic lymphocytic leukemia(CLL) patients in the first affiliated hospital of Nanjing Medical University from January 2016 to December 2020 were included in the retrospective analysis. Among them, there were 106 males and 50 females, with a median age of 60.7 (53.4, 66.0) years old.Serum sample was collected, serum free light chains were detected, and patients were divided into a treatment group (106 cases) and a follow-up group (50 cases) based on the presence of treatment indications.The threshold of serum free light chain(sFLC) was defined by the reference range of the instruction manual and ROC curve. Three indicators were used, including sFLCR, sFLC(κ+λ) and sFLC(κ-λ). Patients were divided into normal sFLCR group ( n=61)and abnormal group( n=95), as well as sFLC (κ+λ) low value group ( n=88) and high value group ( n=68), and sFLC (κ-λ) low value group ( n=64) and high value group ( n=92).The abnormal group and high value group were enrolled as the experimental group, while the normal group and low value group were enrolled as control group. Chi-square test and Fisher′s exact test were used to compare the clinical data, cytogenetics, and molecular biology characteristics of patients in two groups, Kaplan-Meier method was used to analyze the median treatment-free survival (TFS) of the patients, and Cox regression was used to screen the prognostic factors of the patients. Results:The proportion of Rai stage Ⅰ-Ⅳ ( χ2=8.16, P<0.05 and χ2=7.63, P<0.05 and χ2=5.45, P<0.05), Binet stage B-C( χ2=4.11, P<0.05 and χ2=9.43, P<0.05 and χ2=7.34, P<0.05), β 2-microglobulin>3.5 mg/L( χ2=5.13, P<0.05 and χ2=18.3, P<0.05 and χ2=12, P<0.05), ATM gene mutation rate( χ2=6.21, P<0.05 and χ2=4.88, P<0.05 and χ2=5.19, P<0.05), and immunoglobulin heavy chain variable region (IGHV) mutation free rate ( χ2=18.9, P<0.05 and χ2=24.6, P<0.05 and χ2=10.4, P<0.05)in the experimental group were significantly higher than that in control group 1 ( P<0.05). Multivariate analysis indicated that sFLC(κ+λ) ( HR=1.615,95% CI 1.012-2.576, P=0.044), β 2-microglobulin>3.5 mg/L( HR=2.103,95% CI 1.356-3.262, P=0.001) and TP53 deletion and/or mutation( HR=1.892,95% CI 1.082-3.308, P=0.025) were independent prognostic factors affecting the patients time to first treatment(TFT). Conclusions:Serum free light chains can predict the risk of early treatment and have good prognostic significance in newly diagnosed CLL patients.

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.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*