Tailored lipid nanoparticles (LNPs)-mediated small interfering RNA (siRNA) nanomedicines show promise in treating liver disease, such as acute liver injury (ALI) and non-alcoholic steatohepatitis (NASH). However, constructing LNPs that address biosafety concerns, ensure efficient delivery, and target specific hepatic subcellular fractions has been challenging. To evade above obstacles, we develop three novel self-degradable "gemini-like" ionizable lipids (SS-MA, SS-DC, SS-MH) by incorporating disulfide bonds and modifying the length of ester bond and tertiary amino head. Our findings reveal that the disulfide-bond-bridged LNPs exhibit reduction-responsive drug release, improving both biosafety and siRNA delivery efficiency. Furthermore, the distance of ester bond and tertiary amino head significantly influences the LNPs' pK _a, thereby affecting endosomal escape, hemolytic efficiency, absorption capacity of ApoE, uptake efficiency of hepatocytes and liver accumulation. We also develop the modified-mannose LNPs (M-LNP) to target liver macrophages specifically. The optimized M-MH_LNP@TNFα exhibits potential in preventing ALI by decreasing tumor necrosis factor α (TNFα) levels in the macrophages, while MH_LNP@DGAT2 could treat NASH by selectively degrading diacylglycerol O-acyltransferase 2 (DGAT2) in the hepatocytes. Our findings provide new insights into developing novel highly effective and low-toxic "gemini-like" ionizable lipids for constructing LNPs, potentially achieving more effective treatment for hepatic diseases.

Objective: To explore the effect of HIF-1α on osteogenic-angiogenic coupling response in bone mesenchymal stem cells (BMSCs) and provide new concepts for engineered bone tissue in vitro. Methods: With the approval of the hospital’s experimental animal ethics committee, BMSCs were harvested from Wistar rats. The lentivirus carrying hypoxia-inducible factor-1α (HIF-1α) and empty lentivirus were stably transfected into the third generations of BMSCs to form LV-HIF-1α-BMSCs and LV-BMSCs. Meanwhile, BMSCs without transfection of lentivirus were used as a blank control. Then, the effect of HIF-1α transfection was verified by qPCR and Western Blot. LV-HIF-1α-BMSCs were induced to differentiate into endothelium-like cells (iECs). The morphology was observed by optical microscopy, the differentiation rate was detected by cellular flow CD31, and the Transwell test was used to detect the migration ability. At the same time, LV-HIF-1α-BMSCs and LV-BMSCs were continuously cultured to form osteogenic cell sheets (OCTs), which were stained by alkaline phosphatase on day 14 and alizarin red staining on day 21, and counted for mineralization capacity. Finally, iECs were implanted into OCTs to form prevascularized osteogenic cell sheets (P-OCTs), immunofluorescence CD31 was performed to detect the formation of vascular networks, and the results were recorded on days 1, 3, 7, and 14. Meanwhile, osteopontin (OPN) and osteocalcin (OCN) were detected by western blot to verify their ability for osteogenic differentiation on days 1, 7, and 14. Results: The optimal multiplicity of infection (MOI) for lentiviral transfection was 30, and the transfection efficiency was >80%. The results of qPCR and western blot showed that compared with the LV-BMSCs group and BMSCs group, the LV-HIF-1α-BMSCs group had stable and high expressions of HIF-1α (P<0.05). LV-HIF-1α-BMSCs showed an enhanced ability to differentiate into endothelial cells, with a differentiation rate as high as 91.81%. Transwell assay verified that HIF-1α could recruit iECs in vitro. Alkaline phosphatase staining and alizarin red staining confirmed that OCTs formed by LV-HIF-1α-BMSCs had a statistically significant osteogenic differentiation ability compared with LV -BMSCs control group (P<0.05). When iECs were implanted into the LV-HIF-1α-BMSCs group OCTs to form P-OCTs, iECs substantially proliferated and rapidly fused, and formation of the progressive lumen was revealed by immunofluorescent CD31 staining. The expressions of OPN and OCN were significantly enhanced compared with those of the LV-BMSCs control group; OCN was the highest on day 7, and OPN was the highest on day 1 (P<0.05). Conclusion BMSCs transfected by HIF-1α have good osteogenic-angiogenic effect after induction and differentiation, which provides experimental foundation for optimizing the construction of three-dimensional prevascularized bone tissue.

The transcriptome sequencing based on Illumina Novaseq 6000 Platform was performed with the untreated seed embryo(DS), stratified seed embryo(SS), and germinated seed embryo(GS) of Zanthoxylum nitidum, aiming to explore the molecular mechanism regulating the seed dormancy and germination of Z. nitidum and uncover key differentially expressed genes(DEGs). A total of 61.41 Gb clean data was obtained, and 86 386 unigenes with an average length of 773.49 bp were assembled. A total of 29 290 DEGs were screened from three comparison groups(SS vs DS, GS vs SS, and GS vs DS), and these genes were annotated on 134 Kyoto Encyclopedia of Genes and Genomes(KEGG) pathways. KEGG enrichment analysis revealed that the plant hormone signal transduction pathway is the richest pathway, containing 226 DEGs. Among all DEGs, 894 transcription factors were identified, which were distributed across 34 transcription factor families. These transcription factors were also mainly concentrated in plant hormone signal transduction and mitogen-activated protein kinase(MAPK) signaling pathways. Further real-time quantitative polymerase chain reaction(RT-qPCR) validation of 12 DEGs showed that the transcriptome data is reliable. During the process of seed dormancy release and germination, a large number of DEGs involved in polysaccharide degradation, protein synthesis, lipid metabolism, and hormone signal transduction were expressed. These genes were involved in multiple metabolic pathways, forming a complex regulatory network for dormancy and germination. This study lays a solid foundation for analyzing the molecular mechanisms of seed dormancy and germination of Z. nitidum.
Zanthoxylum/metabolism* ; Plant Dormancy/genetics* ; Seeds/metabolism* ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism* ; Transcriptome ; Gene Expression Profiling ; Germination ; Transcription Factors/metabolism* ; Plant Growth Regulators/genetics* ; Signal Transduction

Network pharmacology and molecular docking were employed to predict the mechanism of Zhizhu Decoction in regulating macrophage polarization to reduce adipose tissue inflammation in obese children, and animal experiments were then carried out to validate the prediction results. The active ingredients and targets of Zhizhu Decoction were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP). The inflammation related targets in the adipose tissue of obese children were searched against GeneCards, OMIM, and DisGeNET, and a drug-disease-target network was established. STRING was used to construct a protein-protein interaction(PPI) network and screen for core targets. R language was used to carry out Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses. AutoDock was used for the molecular docking between core targets and active ingredients. 24 SPF grade 6-week C57B/6J male mice were adaptively fed for 1 week, and 8 mice were randomly selected as the blank group. The remaining 16 mice were fed with high-fat diet for 8 weeks to onstruct a high-fat diet induced mouse obesity model. After successful modeling, the 16 mice were randomly divided into model group and Zhizhu Decoction group, with 8 mice in each group. Zhizhu Decoction group was intervened by gavage for 14 days, once a day. Blank group and model group were given an equal amount of sterile double distilled water(ddH_2O) by gavage daily. After the last gavage, serum and inguinal adipose tissue were collected from mice for testing. The morphology of inguinal adipose tissue was observed by hematoxylin-eosin(HE) staining, the levels of inflammatory factors interleukin-6(IL-6) and tumor necrosis factor-α(TNF-α)were detected by enzyme-linked immunosorbent assay(ELISA), and the protein expression of macrophage marker molecule nitric oxide synthase(iNOS) and epidermal growth factor like hormone receptor 1(F4/80) was detected by immunofluorescence staining. Network pharmacology predicted luteolin, naringenin, and nobiletin as the main active ingredients in Zhizhu Decoction and 15 core targets. KEGG pathway enrichment analysis revealed involvement in the key signaling pathway of nuclear factor κB(NF-κB). Molecular docking showed that the active ingredients of Zhizhu Decoction bound well to the core targets. Animal experiment showed that compared with the model group, Zhizhu Decoction reduced the distribution of inflammatory cytokines in the inguinal adipose tissue of mice, lowered the levels of TNF-α and IL-6 in the serum(P<0.05, P<0.01), and down-regulated the expression of iNOS and F4/80(P<0.05). The results showed that the active ingredients in Zhizhu Decoction, such as luteolin, naringenin, and nobiletin, inhibit the aggregation of macrophages in adipose tissue, downregulate their classic activated macrophage(M1) polarization, reduce the expression of inflammatory factors IL-6 and TNF-α, and thus improve adipose tissue inflammation in obese mice.
Animals ; Drugs, Chinese Herbal/pharmacology* ; Molecular Docking Simulation ; Adipose Tissue/immunology* ; Mice ; Male ; Humans ; Network Pharmacology ; Macrophages/immunology* ; Mice, Inbred C57BL ; Child ; Protein Interaction Maps/drug effects* ; Obesity/genetics* ; Inflammation/drug therapy*

Forsythia suspensa is a traditional Chinese medicine and a commonly used landscaping plant. Its dried fruit is used in medicine for its functions of clearing heat, removing toxins, reducing swelling, dissipating masses, and dispersing wind and heat. It possesses extremely high medicinal and economic value. However, the genetic differentiation and diversity of its wild populations remain unclear. In this study, chloroplast genome sequences were obtained from 15 wild individuals of F. suspensa using high-throughput sequencing technology. The sequence characteristics and intraspecific variations were analyzed. The results were as follows:(1) The full length of the F. suspensa chloroplast genome ranged from 156 184 to 156 479 bp, comprising a large single-copy region, a small single-copy region, and two inverted repeat regions. The chloroplast genome encoded a total of 132 genes, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes.(2) A total of 166-174 SSR loci, 792 SNV loci, and 63 InDel loci were identified in the F. suspensa chloroplast genome, indicating considerable genetic variation among individuals.(3) Population structure analysis revealed that F. suspensa could be divided into five or six groups. Both the population structure analysis and phylogenetic reconstruction results indicated significant genetic variation within the wild populations of F. suspensa, with no obvious correlation between intraspecific genetic differentiation and geographical distribution. This study provides new insights into the genetic diversity and differentiation within F. suspensa species and offers additional references for the conservation of species diversity and the utilization of germplasm resources in wild F. suspensa.
Genome, Chloroplast ; Forsythia/classification* ; Phylogeny ; Genetic Variation ; Chloroplasts/genetics* ; Microsatellite Repeats

Objective To evaluate the value of a nomogram model based on ultrasonographic features and inflammatory indicators in the preoperative noninvasive prediction of pathological grading of urothelial carcinoma of bladder(UCB).Methods A retrospective analysis was conducted on 471 patients with pathologically confirmed UCB,and the patients were assigned to high-grade group(401 cases)or low-grade group(70 cases).Basic clinical data(gender,age,macroscopic hematuria),ultrasonographic features(lesion location,blood flow signal,etc.),and blood inflammatory indicators(e.g.neutrophil-to-lymphocyte ratio[NLR])were collected.Independent predictors were screened using univariate and multivariate logistic regression,and a nomogram model was constructed.Model performance was evaluated using the receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DCA).Results Multivariate logistic analysis identified gender(odds ratio[OR]=2.68),age(OR=1.08),macroscopic hematuria(OR=3.19),lesion located in the trigone(OR=4.59),positive blood flow signal(OR=2.87),and NLR(OR=1.03)were independent predictors of high-grade UCB(all P＜0.05).The combined model(clinical features+ultrasonographic characteristics+inflammatory indicators)achieved an area under curve(AUC)of 0.892,which was significantly higher than the clinical feature-only model(AUC=0.799)and the clinical+ultrasonographic model(AUC=0.856).The calibration curve demonstrated good consistency between predicted and actual outcomes,and DCA confirmed its optimal clinical net benefit.Conclusion The nomogram model integrating clinical features,ultrasonographic characteristics,and inflammatory indicators can effectively discriminate UCB pathological grading,providing a reliable preoperative noninvasive assessment tool for personalized treatment decisions.

The efficient,precise,and rapid detection of trace copper ions(Cu2+)is of paramount importance in the realms of food safety,environmental monitoring,and medical health.By ingeniously utilizing the chemical properties of benzotriazole compounds in copper protection,and introducing an electrochemical reduction strategy,a silver nanoparticle composite structure supported by a nickel foam substrate was developed as an active platform for surface-enhanced Raman scattering(SERS)detection.This platform employed benzotriazole-5-carboxylic acid(BTAC)as a specific SERS probe molecule to achieve sensitive analysis of metal ion concentrations.The detection mechanism revealed a highly selective coordination between the Cu2+and the nitrogen atom in the triazole ring of BTAC,triggering subtle structural changes in the triazole ring.This was manifested by a significant and quantifiable shift in the characteristic peak of the SERS spectrum(particularly at 1001 cm-1),with a maximum shift of up to 30 cm-1.This phenomenon not only addressed the issue of reproducibility in quantitative analysis caused by the non-uniformity of SERS substrate materials but also significantly broadened the application boundaries of SERS technology for trace metal ion detection.It enabled ultra-sensitive detection of Cu2+concentrations ranging from 1×10-6 to 1×10-11 mol/L,with a detection limit as low as 1×10-11 mol/L,significantly enhancing detection sensitivity and accuracy.This work provided a novel and efficient strategy for rapid detection of trace Cu2+and enriched the application potential of SERS technology in food safety,environmental monitoring and biomedical analysis.

Objective To establish and evaluate a nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer.Methods A retrospective study was conducted on 1298 patients with HBV-related primary liver cancer hospitalized in the Kunming Third People's Hospital from January 2012 to December 2022.General data and serological indicators were collected,and patients were divided into infection group(n=262)and control group(n=1036)based on the occurrence of spontaneous peritonitis.Univariate and LASSO regression analyses were used to screen variables,followed by binary logistic regression to analyze the influencing factors of spontaneous peritonitis in HBV-related primary liver cancer patients,leading to the establishment of a nomogram prediction model.Finally,the Hosmer-lemeshow(H-L)goodness of fit test,receiver operating characteristic(ROC)curve,calibration curve,decision curve analysis(DCA)and clinical impact curve(CIC)were utilized to evaluate the fit degree,accuracy,calibration,and clinical practicability of the nomogram prediction model.Results Single factor analysis revealed significant differences between infection group and control group in portal vein cancer thrombus(PVTT),Child-Pugh grade,China Liver Cancer Staging(CNLC)stage,alcohol consumption history,smoking history,white blood cell count(WBC),neutrophil count(NE),hemoglobin(Hb),fibrinogen(FIB),abnormal prothrombin(PIVKA-Ⅱ),aspartate aminotransferase(AST),alanine aminotransferase(ALT),total protein(TP),prealbumin(PA),γ-glutamyltransferase(GGT),alkaline phosphatase(ALP),cholinesterase(CHE),total bile acid(TBA),total cholesterol(TC),low density lipoprotein(LDL),creatinine(Cr),HBV DNA,CD3+T cells count,CD4+T cells count,CD8+T cells count,CD4+T cells/CD8+T cells ratio,procalcitonin(PCT),serum amyloid A(SAA),interleukin-6(IL-6),high-sensitivity C-reactive protein(hs-CRP),alpha-fetoprotein(AFP),and IL-4(P＜0.05).LASSO regression analysis identified 5 variables:Child-Pugh grade,PVTT,WBC,CHE and hs-CRP.Binary logistic regression analysis indicated that Child-Pugh grade(Grade B:OR=5.780,95％CI 3.271-10.213,P＜0.001;Grade C:OR=14.818,95％CI 7.697-28.526,P＜0.001),PVTT(OR=2.893,95％CI 2.037-4.108,P＜0.001),WBC(OR=1.088,95％CI 1.031-1.148,P=0.002),and hs-CRP(OR=1.005,95％CI 1.001-1.010,P=0.026)were the independent risk factors of spontaneous peritonitis in HBV-related primary liver cancer patients.Using these 4 variables,a nomogram prediction model was constructed and evaluated.The P-value of the H-L goodness of fit test was 0.760.Moreover,the area under ROC curve(AUC)was 0.866,with a sensitivity of 0.870 and a specificity of 0.716.The average absolute error of the calibration curve is 0.022.DCA and CIC analyses demonstrated that the nomogram prediction model possessed some clinical utility.Conclusion The nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer patients,constructed using Child-Pugh grade,PVTT,WBC and hs-CRP,exhibits a high fitting degree and accuracy,with the prediction probability highly consistent with the actual occurrence probability,and possesses certain clinical practicability.