ObjectiveTo investigate the effects of Huangqi Jianzhongtang （HQJZ） on macrophage polarization and fat consumption in cancer cachexia （CC） mice. MethodsUltra-performance liquid chromatography-quadrupole/electrostatic field Orbitrap high-resolution mass spectrometry （UPLC-Q-Orbitrap HRMS） was used to control the quality of HQJZ. （1） In vitro experiment： HQJZ-containing serum was prepared， and the optimal concentration was determined by cytotoxicity assay. Mouse monocyte-derived macrophages （RAW264.7） were cultured and randomly divided into six groups， including a blank group， a classically activated macrophages （M1） group， an alternatively activated macrophages （M2） group， a HQJZ + blank group， a HQJZ+M1 group， and a HQJZ + M2 group. The relative expression of macrophage marker genes CD86， inducible nitric oxide synthase （iNOS）， CD206， and arginase-1 （Arg1） was detected by real-time quantitative polymerase chain reaction （Real-time PCR ）. （2） In vivo experiment： Thirty-two BALB/c mice were randomly divided into a control group， a model group， a medroxyprogesterone acetate （MPA） group， and a HQJZ group. Except for the control group， the other mice were injected with CT-26 colon cancer cells to establish a CC model. Mice in the MPA and HQJZ groups were given MPA （0.13 g·kg^-1·d^-1） or HQJZ （13.13 g·kg^-1·d^-1） by gavage， respectively， while mice in the control and model groups were given an equal volume of saline by gavage， with interventions continued for 10 d. Real-time PCR was used to detect the expression of macrophage markers （iNOS， Arg1， CD86， CD206） and fat browning-related genes uncoupling protein 1 （UCP1） and peroxisome proliferator-activated receptor γ （PPARγ） in epididymal adipose tissue. Western blot （WB） was used to detect protein expression levels of UCP1 and PPARγ. Micro-computed tomography （micro-CT） was used to measure residual fat volume， and hematoxylin-eosin （HE） staining was used to assess fat browning and calculate pathological scores. ResultsIn vitro， the dominant effective concentration of HQJZ-containing serum was 12.5%. Real-time PCR results showed that， compared with the blank group， Arg1 expression decreased in the HQJZ+blank group （P<0.05）， CD206 showed a downward trend without statistical significance， while iNOS and CD86 expression were significantly increased （P<0.05）. Compared with the M1 group， Arg1 and CD206 expression decreased in the HQJZ+M1 group （P<0.05）. Compared with the M2 group， CD206 expression decreased in the HQJZ+M2 group （P<0.05）， CD86 expression increased significantly （P<0.01）. In vivo， Real-time PCR results showed that， compared with the control group， CD86 and CD206 expression levels were significantly increased in the model group （P<0.01）. Compared with the model group， CD206 expression in the MPA group was significantly decreased （P<0.01）. In the HQJZ group， CD206 was significantly decreased （P<0.01）. WB results showed that， compared with the model group， protein expression of UCP1 and PPARγ was significantly reduced in the HQJZ group （P<0.05， P<0.01）. micro-CT results showed that the total white fat volume in the HQJZ group was greater than that in the model group （P<0.05）. HE staining results showed that pathological scores in the HQJZ group were lower than those in the model group （P<0.05）. ConclusionHQJZ may inhibit white adipose tissue browning by promoting macrophage M1 polarization and suppressing M2 polarization， thereby delaying fat consumption in CC mice.

ObjectiveTo investigate the effects of rhizosphere organic acids secreted by the roots of Salvia miltiorrhiza on continuous cropping obstacles. MethodsThe mixed solution of organic acids in the rhizosphere of S. miltiorrhiza in continuous cropping and rotation cropping was added to the hairy roots subcultured for 21 days， and samples were collected on days 0， 2， 4， 6， 8， and 10. The changes of biomass， effective components， primary metabolites， secondary metabolites， antioxidant enzymes， and hormones in hairy roots of S. miltiorrhiza were observed and determined. ResultsCompared with the rotation cropping group and the blank control group， the simulation of organic acid secretion from the roots of S. miltiorrhiza had a significant inhibitory effect on the growth of hairy roots and decreased the content of effective components as well as total sugar and total protein in primary metabolites. Compared with the blank control group， the rotation cropping group and the continuous cropping group showed total sugar and total protein content decreases of 33.9% and 5.1%， respectively. On the other hand， the secretion of organic acids from S. miltiorrhiza roots significantly promoted the accumulation of total phenolic acids and total tanshinone， which showed increases of 14.6% and 1.6%， respectively， in continuous cropping group and rotation cropping group compared with the blank control group. ConclusionThe organic acid environment under continuous cropping significantly inhibited the growth of hairy roots and the accumulation of primary metabolites， while promoting the synthesis and accumulation of secondary metabolites of S. miltiorrhiza.

Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the "therapeutic module" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

Increasing evidence showed that histone deacetylase 6 (HDAC6) dysfunction is directly associated with the onset and progression of various diseases, especially cancers, making the development of HDAC6-targeted anti-tumor agents a research hotspot. In this study, artificial intelligence (AI) technology and molecular simulation strategies were fully integrated to construct an efficient and precise drug screening pipeline, which combined Voting strategy based on compound-protein interaction (CPI) prediction models, cascade molecular docking, and molecular dynamic (MD) simulations. The biological potential of the screened compounds was further evaluated through enzymatic and cellular activity assays. Among the identified compounds, Cmpd.18 exhibited more potent HDAC6 enzyme inhibitory activity (IC₅₀ = 5.41 nM) than that of tubastatin A (TubA) (IC₅₀ = 15.11 nM), along with a favorable subtype selectivity profile (selectivity index ≈ 117.23 for HDAC1), which was further verified by the Western blot analysis. Additionally, Cmpd.18 induced G2/M phase arrest and promoted apoptosis in HCT-116 cells, exerting desirable antiproliferative activity (IC₅₀ = 2.59 μM). Furthermore, based on long-term MD simulation trajectory, the key residues facilitating Cmpd.18's binding were identified by decomposition free energy analysis, thereby elucidating its binding mechanism. Moreover, the representative conformation analysis also indicated that Cmpd.18 could stably bind to the active pocket in an effective conformation, thus demonstrating the potential for in-depth research of the 2-(2-phenoxyethyl)pyridazin-3(2H)-one scaffold.

Diabetic retinopathy, a prevalent and vision-threatening microvascular complication of diabetes mellitus, is the leading cause of blindness among middle-aged and elderly individuals. Natural diterpenoids isolated from Siegesbeckia pubescens demonstrate potent anti-inflammatory properties. This study aimed to identify novel bioactive diterpenoids from S. pubescens and investigate their effects on oxidative stress and inflammatory responses in diabetic retinopathy, both in vitro and in vivo. Three new ent-pimarane-type diterpenoids (1-3) and six known compounds (4-9) were isolated from the aerial parts of S. pubescens. Their structures were elucidated through spectroscopic data interpretation, and absolute configurations were determined by comparing calculated and experimental electronic circular dichroism (ECD) spectra. Among these compounds, 14β,16-epoxy-ent-3β,15α,19-trihydroxypimar-7-ene (5) exhibited the most potent protective effect against high glucose and interleukin-1β (IL-1β)-stimulated human retinal endothelial cells. Mechanistically, compound 5 promoted endothelial cell survival while ameliorating oxidative stress and inflammatory response in diabetic retinopathy, both in vivo and in vitro. These findings not only suggest that diterpenoids such as compound 5 are important anti-inflammatory constituents in S. pubescens, but also indicate that compound 5 may serve as a lead compound for preventing or treating vascular complications associated with diabetic retinopathy.
Diabetic Retinopathy/metabolism* ; Humans ; Oxidative Stress/drug effects* ; Animals ; Diterpenes, Kaurane/administration & dosage* ; Asteraceae/chemistry* ; Male ; Endothelial Cells/drug effects* ; Abietanes/administration & dosage* ; Molecular Structure ; Mice ; Anti-Inflammatory Agents/chemistry* ; Plant Extracts/chemistry* ; Mice, Inbred C57BL

OBJECTIVE To investigate the effects of Buyang huanwu decoction on red blood cells in hyperlipidemia model mice. METHODS Male C57BL/6 mice were fed a high-fat diet to prepare a hyperlipidemia model. Successfully modeled mice were randomly assigned to the model group， atorvastatin calcium group （0.26 g/kg）， fenofibrate group （1.3 mg/kg）， and high-， medium-， and low- dose groups of Buyang huanwu decoction （18.6， 9.3， 4.6 g/kg）， with 10 mice in each group. Additionally， 10 mice fed with regular chow served as the normal group. Each group of mice received intragastric administration with the corresponding drug or normal saline once daily for 21 consecutive days. After the last administration， the body weight of the mice in each group was measured， and blood glucose， total cholesterol （TC）， triglyceride （TAG）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C） levels were measured. Red blood cell morphology changes were observed， and the expression levels of glucose transporter type 1 （GLUT1）， erythrocyte membrane protein band 4.2 （protein 4.2）， caveolin-1， and flotillin-1 in erythrocyte membrane were determined. RESULTS Compared with the model group， the body weight and levels of TC， TAG， HDL-C， LDL-C， and the expression levels of GLUT1， caveolin-1 and flotillin-1 in the Buyang huanwu decoction groups were significantly decreased， while blood glucose levels and the expression levels of protein 4.2 were significantly increased （P＜0.05）. The red blood cell morphology in the low- and medium-dose groups of Buyang huanwu decoction was significantly promoted. CONCLUSIONS Buyang huanwu decoction can reduce blood lipid levels in hyperlipidemia model mice and strengthen the morphology and function of red blood cells in a hyperlipidemic environment， which has the potential to be used for preventing hyperlipidemia complications such as atherosclerosis.

OBJECTIVE To establish a rapid analytical method to identify the chemical components in Xitong preparations for the treatment of rheumatoid arthritis by ultra-high performance liquid chromatography coupled triple time-of-flight mass spectrometry(UPLC-Triple-TOF-MS/MS). METHODS The analysis was performed on an ACQUITY UPLC HSS T3 (2.1 mm×150 mm, 1.8 μm) column with the mobile phase consisting of water containing 0.1% formic acid(A) and acetonitrile containing 0.1% formic acid(B) in gradient mode at a flow rate of 0.3 mL·min−1. Data acquisition was carried out under positive and negative ion modes. The processed data was analyzed by Peakview software and compound database. The chemical components were determined by comparison with standard products, combining with the characteristic fragments in secondary MS, and those in the related literatures. RESULTS Seventy-eight compounds were identified including 20 phenylpropanoids, 33 terpenes, 19 flavonoids, 6 oxylipins, two of which might be new compounds. CONCLUSION The method can be used for rapid identification of chemical compositions in Xitong preparations, which provides basis for quality control and elucidation of phamarcodynamic material basis of Xitong pills and capsules .

Objective:To assess the value of serum tumor specific protein 70 (SP70) for prognostic stratification in acute myeloid leukemia (AML).Methods:A cohort study design was adopted. 129 newly diagnosed AML patients from September 2022 to January 2024 at the Hematology Department of the First Affiliated Hospital of Nanjing Medical University were included, as well as a control group consisted of 120 healthy individuals and 7 cases with benign hematologic diseases during the same period (total 127 cases). Clinical data were collected from Electronic Medical Records. According to the 2023 edition of the Chinese Leukemia Diagnosis and Treatment Guidelines, AML patients with good or moderate prognosis were categorized as low-to-intermediate risk, while those with poor prognosis were high-risk group. Univariate and multivariate logistic regression analyses were used to identify variables significantly associated with AML prognostic risk. ROC analysis was used to evaluate diagnostic performance. A nomogram for predicting patient prognostic risk was constructed by R 4.0.2 software, and the internal validation was performed using bootstrapping.Results:Among 129 AML patients, there were 71 males (55.0%) and 58 females (45.0%), with 42 (32.6%) classified as high-risk and 87 (67.4%) as low-intermediate risk. The high-risk group had a significantly higher median age [62 (48, 67) years] compared to the low-intermediate risk group [50 (35, 63) years, Z=-2.381, P=0.017], and a significantly higher proportion of males (30 patients, 71.4%) compared to the low-intermediate risk group (41 patients, 47.1%, χ 2=6.760, P=0.009). Multivariate logistic regression analysis indicated that serum SP70 ( OR=2.54, 95% CI: 1.68-3.84, P<0.001), hemoglobin (HB) ( OR=0.96, 95% CI: 0.93-0.99, P<0.05), and bone marrow blast (BM blast) ( OR=1.07, 95% CI: 1.02-1.13, P<0.05) were independent risk factors for high-risk prognosis in AML patients. ROC analysis showed that the area under the curve (AUC) for SP70 predicting high-risk patients was 0.908 (cut-off value of 5.74 ng/ml, 95% CI: 0.845-0.952, sensitivity 90.5%, specificity 82.8%). The combined model of serum SP70, HB, and BM blasts had an AUC of 0.931 (95% CI: 0.890-0.973); C-index=0.925 (95% CI: 0.876-0.963),with no statistically significant difference compared to serum SP70 alone ( Z=1.693, P>0.05). Conclusion:Serum SP70 may be a promising non-invasive molecular biomarker for prognostic stratification in AML.

Objective:To assess the value of serum tumor specific protein 70 (SP70) for prognostic stratification in acute myeloid leukemia (AML).Methods:A cohort study design was adopted. 129 newly diagnosed AML patients from September 2022 to January 2024 at the Hematology Department of the First Affiliated Hospital of Nanjing Medical University were included, as well as a control group consisted of 120 healthy individuals and 7 cases with benign hematologic diseases during the same period (total 127 cases). Clinical data were collected from Electronic Medical Records. According to the 2023 edition of the Chinese Leukemia Diagnosis and Treatment Guidelines, AML patients with good or moderate prognosis were categorized as low-to-intermediate risk, while those with poor prognosis were high-risk group. Univariate and multivariate logistic regression analyses were used to identify variables significantly associated with AML prognostic risk. ROC analysis was used to evaluate diagnostic performance. A nomogram for predicting patient prognostic risk was constructed by R 4.0.2 software, and the internal validation was performed using bootstrapping.Results:Among 129 AML patients, there were 71 males (55.0%) and 58 females (45.0%), with 42 (32.6%) classified as high-risk and 87 (67.4%) as low-intermediate risk. The high-risk group had a significantly higher median age [62 (48, 67) years] compared to the low-intermediate risk group [50 (35, 63) years, Z=-2.381, P=0.017], and a significantly higher proportion of males (30 patients, 71.4%) compared to the low-intermediate risk group (41 patients, 47.1%, χ 2=6.760, P=0.009). Multivariate logistic regression analysis indicated that serum SP70 ( OR=2.54, 95% CI: 1.68-3.84, P<0.001), hemoglobin (HB) ( OR=0.96, 95% CI: 0.93-0.99, P<0.05), and bone marrow blast (BM blast) ( OR=1.07, 95% CI: 1.02-1.13, P<0.05) were independent risk factors for high-risk prognosis in AML patients. ROC analysis showed that the area under the curve (AUC) for SP70 predicting high-risk patients was 0.908 (cut-off value of 5.74 ng/ml, 95% CI: 0.845-0.952, sensitivity 90.5%, specificity 82.8%). The combined model of serum SP70, HB, and BM blasts had an AUC of 0.931 (95% CI: 0.890-0.973); C-index=0.925 (95% CI: 0.876-0.963),with no statistically significant difference compared to serum SP70 alone ( Z=1.693, P>0.05). Conclusion:Serum SP70 may be a promising non-invasive molecular biomarker for prognostic stratification in AML.

Objective To investigate the factors influencing rapid neurological improvement(RNI)after mechani-cal thrombectomy(MT)in patients with acute anterior circulation ischemic stroke(AACIS),and to construct a predictive scoring model for RNI.Methods A retrospective study was conducted on 312 AAIS patients treated with MT at the South-west Hospital and the Zigong Third People's Hospital from January 2017 to October 2021.Univariate analysis and multi-variate logistic regression analysis were performed to identify the independent factors influencing RNI.A scoring model for RNI prediction was established by assigning scores to significant variables in multivariate analysis.The prediction value was evalu-ated using the receiver operating characteristic(ROC)curve.Results Among the 312 AACIS patients,159(50.96%)dem-onstrated RNI.Multivariate logistic regression analysis showed that history of diabetes mellitus[odds ratio(OR)=0.518;95%confidence interval(CI)0.290-0.926;P=0.027]and Van Swieten score(3-4 points)(OR=0.537;95%CI 0.294-0.981;P=0.043)were independent risk factors for RNI in AACIS patients after MT.However,mTICI(grade 2b or 3)was an inde-pendent protective factor for RNI in patients with AACIS(OR=3.912;95%CI 1.706-8.982;P=0.001).The area under the ROC curve of the predictive scoring model was 0.628(95%CI 0.565-0.690;P<0.001).The optimal cut-off value was 3 points,the sensitivity was 68.39%,and the specificity was 52.98%.Conclusion The predictive scoring model consisting of history of diabetes mellitus,preoperative Van Swieten score,and postoperative mTICI grade is valuable in predicting RNI in patients with AACIS after MT.