Objective: To elucidate the pharmacological material basis of Danggui Buxue Decoction for its "blood-tonifying" effect through spectrum-effect relationship analysis.
Methods: The chemical constituents of Danggui Buxue Decoction were qualitatively analyzed using liquid chromatography-quadrupole-orbitrap mass spectrometry (LC-QE/MS). An ultra-performance liquid chromatography (UPLC) fingerprint of Danggui Buxue Decoction was established, and the common peaks of 30 batches of self-made Danggui Buxue Decoction were quantitatively analyzed. A zebrafish anemia model induced by phenylhydrazine was established, and the spectrum-effect relationship analysis method was applied to correlate the pharmacological data of 30 batches of Danggui Buxue Decoction with the fingerprint data to screen for its pharmacological material basis.
Results: A total of 90 prototype components were identified in the qualitative analysis of Danggui Buxue Decoction. The UPLC fingerprint of Danggui Buxue Decoction and the zebrafish anemia model were successfully established. The spectrum-effect relationship analysis of the pharmacological data and fingerprint data of 30 batches of Danggui Buxue Decoction revealed that the pharmacological materials of Danggui Buxue Decoction included 4-guanidinobutanoic acid (from Astragalus), isoleucine (from wine-prepared Angelica), lauric acid (from wine-prepare Angelica), ferulic acid (from both wine-prepared Angelica and Astragalus), 6-methoxy-2H-chromen-2-one (from both wine-prepared Angelica and Astragalus), sophoraisoflavone glucoside (from both wine-prepared Angelica and Astragalus), and an unknown peak 8.
Conclusion: This study screened the pharmacological material basis of Danggui Buxue Decoction through qualitative and quantitative analysis of its prototype chemical constituents combined with spectrum-effect relationship analysis, providing scientific support for the clinical application and secondary development of this classic prescription.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

This study aimed to explore the therapeutic mechanisms of Colquhounia Root Tablets(CRT) in treating diabetic kidney disease(DKD) by integrating biomolecular network mining with animal model verification. By analyzing clinical transcriptomics data, an interaction network was constructed between candidate targets of CRT and DKD-related genes. Based on the topological eigenvalues of network nodes, 101 core network targets of CRT against DKD were identified. These targets were found to be closely related to multiple pathways associated with type 2 diabetes, immune response, and metabolic reprogramming. Given that immune-inflammatory imbalance driven by metabolic reprogramming is one of the key pathogenic mechanisms of DKD, and that many core network targets of CRT are involved in this pathological process, receptor for advanced glycation end products(RAGE)-reactive oxygen species(ROS)-phosphatidylinositol 3-kinase(PI3K)-protein kinase B(AKT)-nuclear factor-κB(NF-κB)-NOD-like receptor family pyrin domain containing 3(NLRP3) signaling axis was selected as a candidate target for in-depth research. Further, a rat model of DKD induced by a high-sugar, high-fat diet and streptozotocin was established to evaluate the pharmacological effects of CRT and verify the expression of related targets. The experimental results showed that CRT could effectively correct metabolic disturbances in DKD, restore immune-inflammatory balance, and improve renal function and its pathological changes by inhibiting the activation of the RAGE-ROS-PI3K-AKT-NF-κB-NLRP3 signaling axis. In conclusion, this study reveals that CRT alleviates the progression of DKD through dual regulation of metabolic reprogramming and immune-inflammatory responses, providing strong experimental evidence for its clinical application in DKD.
Animals ; Diabetic Nephropathies/metabolism* ; Receptor for Advanced Glycation End Products/genetics* ; NF-kappa B/genetics* ; Signal Transduction/drug effects* ; Rats ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Proto-Oncogene Proteins c-akt/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Phosphatidylinositol 3-Kinases/genetics* ; Reactive Oxygen Species/metabolism* ; Humans ; Plant Roots/chemistry* ; Rats, Sprague-Dawley ; Tablets/administration & dosage*

Objective:To investigate the expression characteristics of Zeste enhancer of Zeste homolog 2 (EZH2) in breast cancer tissue and its influence on tumor progression and prognosis.Methods:Transcriptome data of breast cancer tissue and normal breast tissue adjacent to cancer as well as clinical data of patients were obtained from the cancer genome atlas (TCGA) database, gene expression comprehensive database and European genome phenotype archives database, and the difference of EZH2 expression was analyzed using TIMER 2.0 platform. The survival information of breast cancer patients was obtained from the Kaplan Meier Plotter database, and the overall survival time, relapse free survival time and distant metastasis free survival time of breast cancer patients with low EZH2 expression and high EZH2 expression were compared. Select 14 nude mice were selected and randomly divided into si-EZH2 group and control group, with 7 mice in each group.MCF7 culture suspensions transfected with EZH2 knockdown plasmid and control plasmid were inoculated for corresponding group. The body mass and tumor volume of two groups of nude mice inoculated with MCF7 cells were compared at different times. On the 28th day, the nude mice were euthanized and the tumors were dissected to compare the tumor mass of the two groups of nude mice. The normally distributed quantitative data was represented by xˉ ± s. Two independent sample t-tests were used for comparison between two groups, repeated measures ANOVA was used for comparison of body mass and tumor volume between two groups of nude mice at different times, and Bonferroni test was used for pairwise comparison. The comparison of survival rates was conducted using log rank test. Results:A total of 1085 breast cancer tissues and 291 normal adjacent breast tissues were included in the TCGA database. EZH2 expression in breast cancer tissues was higher than that in normal adjacent breast tissues ( P<0.05). In the Kaplan Meier Plotter database, the total survival time, relapse free survival time, and distant metastasis free survival time of breast cancer patients in the EZH2 overexpression group were shorter than those in the EZH2 low expression group ( P=0.013, <0.001, <0.001). After 7 days of inoculation with MCF7 culture suspension, significant subcutaneous tumors were observed on the left back of both groups of nude mice. On the first day, there were no statistically significant difference in body mass between the two groups of nude mice ( P>0.05); On day 7, 13, 19, 25, and 28, the body mass and tumor volume of both groups of nude mice gradually increased (nude mouse body mass: within group F=29.31, P<0.001, between groups F=234.32, P<0.001, Finteraction=16.83, P<0.001; Tumor volume: within group F=34.00, P<0.001, between groups F=193.17, P<0.001, Finteraction=35.61, P<0.001). And the body mass of the siEZH2 group nude mice was higher than that of control group (all P<0.05). On days 19, 25, and 28, tumor the volume of the siEZH2 group nude mice was smaller than that of control group (all P<0.05). On the 28th day, the mass of tumors dissected in the siEZH2 group of nude mice was lower than that in the control group [(0.30±0.07) g vs. (0.61±0.14) g, t=5.16, P<0.001]。 Conclusions:EZH2 is highly expressed in breast cancer tissues and is significantly associated with poor prognosis. Knockdown of EZH2 can significantly inhibit the proliferation and tumor formation of breast cancer cells.

OBJECTIVE To analyze the reasons for the outbreak of suspected carbapenem-resistant Acinetobacter baumannii(CRAB)infections in the neurosurgical intensive care unit to take comprehensive prevention and con-trol measures to control the spread of infections,and to provide a reference for the control of multidrug-resistant organisms(MDRO)infections in intensive care units.METHODS Epidemiological data were collected from five patients with CRAB infections in the neurosurgical intensive care unit of Gansu Provincial People's Hospital in Mar.2024,and environmental hygiene monitoring and comprehensive infection prevention and control measures were conducted.RESULTS A total of five cases of lower respiratory tract infections occurred,all of which were hospital-acquired infections,and all patients had consistent spatial-temporal distribution.A.baumannii was detec-ted in the sputum cultures of all patients,and all were resistant to carbapenems,aminoglycosides and some β-lac-tam drugs.Before the implementation of comprehensive prevention and control measures,a total of 25 samples from the surfaces and the hands of health workers were collected,with a pass rate of 52.00％;CRAB was detected on the surface of treatment carts and the wall of sputum suction bottles in the treatment room,with a detection rate of 8.00％.After the implementation,a total of 24 samples were collected,with a pass rate of 100.00％,and the difference was statistically significant when compared with the pre-implementation period(χ2=16.987,P<0.001).Through the implementation of comprehensive measures such as isolation,standardization of the ward cleaning and disinfection process,strengthening hand hygiene,standardization of sterile operations and personnel management,the indicators such as hand hygiene compliance rate,the execution rate of multi-drug-resistant bac-terial preventive and control measures and the fluorescent marker removal rate were all improved,and the suspec-ted CRAB infection outbreak was timely controlled.CONCLUSION This suspected CRAB hospital-acquired infec-tion outbreak may be related to a variety of factors,and timely environmental hygiene monitoring and comprehen-sive infection prevention and control measures can effectively control the spread of CRAB infection.

Periodontal bone defects, primarily caused by periodontitis, are highly prevalent in clinical settings and manifest as bone fenestration, dehiscence, or attachment loss, presenting a significant challenge to oral health. In regenerative medicine, harnessing developmental principles for tissue repair offers promising therapeutic potential. Of particular interest is the condensation of progenitor cells, an essential event in organogenesis that has inspired clinically effective cell aggregation approaches in dental regeneration. However, the precise cellular coordination mechanisms during condensation and regeneration remain elusive. Here, taking the tooth as a model organ, we employed single-cell RNA sequencing to dissect the cellular composition and heterogeneity of human dental follicle and dental papilla, revealing a distinct Platelet-derived growth factor receptor alpha (PDGFRA) mesenchymal stem/stromal cell (MSC) population with remarkable odontogenic potential. Interestingly, a reciprocal paracrine interaction between PDGFRA⁺ dental follicle stem cells (DFSCs) and CD31⁺ Endomucin⁺ endothelial cells (ECs) was mediated by Vascular endothelial growth factor A (VEGFA) and Platelet-derived growth factor subunit BB (PDGFBB). This crosstalk not only maintains the functionality of PDGFRA⁺ DFSCs but also drives specialized angiogenesis. In vivo periodontal bone regeneration experiments further reveal that communication between PDGFRA⁺ DFSC aggregates and recipient ECs is essential for effective angiogenic-osteogenic coupling and rapid tissue repair. Collectively, our results unravel the importance of MSC-EC crosstalk mediated by the VEGFA and PDGFBB-PDGFRA reciprocal signaling in orchestrating angiogenesis and osteogenesis. These findings not only establish a framework for deciphering and promoting periodontal bone regeneration in potential clinical applications but also offer insights for future therapeutic strategies in dental or broader regenerative medicine.
Receptor, Platelet-Derived Growth Factor alpha/metabolism* ; Humans ; Neovascularization, Physiologic/physiology* ; Dental Sac/cytology* ; Single-Cell Analysis ; Transcriptome ; Mesenchymal Stem Cells/metabolism* ; Bone Regeneration ; Animals ; Dental Papilla/cytology* ; Periodontium/physiology* ; Stem Cells/metabolism* ; Regeneration ; Angiogenesis

Metachromatic leukodystrophy (MLD) is an inherited disease caused by a deficiency of the enzyme arylsulfatase A (ARSA). Lentivirus-modified autologous hematopoietic stem cell gene therapy (HSCGT) has recently been approved for clinical use in pre and early symptomatic children with MLD to increase ARSA activity. Unfortunately, this advanced therapy is not available for most patients with MLD who have progressed to more advanced symptomatic stages at diagnosis. Patients with late-onset juvenile MLD typically present with a slower neurological progression of symptoms and represent a significant burden to the economy and healthcare system, whereas those with early onset infantile MLD die within a few years of symptom onset. We conducted a pilot study to determine the safety and benefit of HSCGT in patients with postsymptomatic juvenile MLD and report preliminary results. The safety profile of HSCGT was favorable in this long-term follow-up over 9 years. The most common adverse events (AEs) within 2 months of HSCGT were related to busulfan conditioning, and all AEs resolved. No HSCGT-related AEs and no evidence of distorted hematopoietic differentiation during long-term follow-up for up to 9.6 years. Importantly, to date, patients have maintained remarkably improved ARSA activity with a stable disease state, including increased Functional Independence Measure (FIM) score and decreased magnetic resonance imaging (MRI) lesion score. This long-term follow-up pilot study suggests that HSCGT is safe and provides clinical benefit to patients with postsymptomatic juvenile MLD.
Humans ; Leukodystrophy, Metachromatic/genetics* ; Pilot Projects ; Genetic Therapy/methods* ; Hematopoietic Stem Cell Transplantation ; Male ; Follow-Up Studies ; Female ; Lentivirus/genetics* ; Child ; Child, Preschool ; Hematopoietic Stem Cells/metabolism* ; Cerebroside-Sulfatase/metabolism* ; Adolescent

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis