Folic acid-mediated hollow Mn 3 O 4 nanocomposites for in vivo MRI/FLI monitoring the metastasis of gastric cancer.

BACKGROUND: Metastasis is one of the main factors leading to the high mortality rate of gastric cancer. The current monitoring methods are not able to accurately monitor gastric cancer metastasis. METHODS: In this paper, we constructed a new type of hollow Mn 3 O 4 nanocomposites, Mn 3 O 4 @HMSN-Cy7.5-FA, which had a size distribution of approximately 100 nm and showed good stability in different liquid environments. The in vitro magnetic resonance imaging (MRI) results show that the nanocomposite has good response effects to the acidic microenvironment of tumors. The acidic environment can significantly enhance the contrast of T 1 -weighted MRI. The cellular uptake and endocytosis results show that the nanocomposite has good targeting capabilities and exhibits good biosafety, both in vivo and in vitro. In a gastric cancer nude mouse orthotopic metastatic tumor model, with bioluminescence imaging's tumor location information, we realized in vivo MRI/fluorescence imaging (FLI) guided precise monitoring of the gastric cancer orthotopic and metastatic tumors with this nanocomposite. RESULTS: This report demonstrates that Mn 3 O 4 @HMSN-Cy7.5-FA nanocomposites is a promising nano-diagnostic platform for the precision diagnosis and therapy of gastric cancer metastasis in the future. CONCLUSIONS: In vivo MRI/FLI imaging results show that the nanocomposites can achieve accurate monitoring of gastric cancer tumors in situ and metastases. BLI's tumor location information further supports the good accuracy of MRI/FLI dual-modality imaging. The above results show that the MHCF NPs can serve as a good nano-diagnostic platform for precise in vivo monitoring of tumor metastasis. This nanocomposite provides more possibilities for the diagnosis and therapy of gastric cancer metastases.

Sacubitril/Valsartan inhibits M1 type macrophages polarization in acute myocarditis by targeting C-type natriuretic peptide.

Studies have shown that Sacubitril/valsartan (Sac/Val) can reduce myocardial inflammation in myocarditis mice, in addition to its the recommended treatment of heart failure. However, the underlying mechanisms of Sac/Val in myocarditis remain unclear. C-type natriuretic peptide (CNP), one of the targeting natriuretic peptides of Sac/Val, was recently reported to exert cardio-protective and anti-inflammatory effects in cardiovascular systems. Here, we focused on circulating levels of CNP in patients with acute myocarditis (AMC) and whether Sac/Val modulates inflammation by targeting CNP in experimental autoimmune myocarditis (EAM) mice as well as LPS-induced RAW 264.7 cells and bone marrow derived macrophages (BMDMs) models. Circulating CNP levels were higher in AMC patients compared to healthy controls, and these levels positively correlated with the elevated inflammatory cytokines IL-6 and monocyte count. In EAM mice, Sac/Val alleviated myocardial inflammation while augmenting circulating CNP levels rather than BNP and ANP, accompanied by reduction in intracardial M1 macrophage infiltration and expression of inflammatory cytokines IL-1ß, TNF-α, and IL-6. Furthermore, Sac/Val inhibited CNP degradation and directly blunted M1 macrophage polarization in LPS-induced RAW 264.7 cells and BMDMs. Mechanistically, the effects might be mediated by the NPR-C/cAMP/JNK/c-Jun signaling pathway apart from NPR-B/cGMP/NF-κB pathway. In conclusion, Sac/Val exerts a protective effect in myocarditis by increasing CNP concentration and inhibiting M1 macrophages polarization.

The role of blood podoplanin in patients with viral myocarditis.

Podoplanin (PDPN), a small mucin-like glycoprotein, was recently found to promote the generation of cardiac ectopic lymphoid follicles and anti-heart autoantibodies (AHA) in viral myocarditis (VMC) mice. Herein, we investigated the blood PDPN expression and its potential clinical value in VMC patients. Overall, 40 VMC patients were enrolled among 112 hospitalized patients with suspected myocarditis. Their serum PDPN levels were higher than those in controlled acute myocardial infarction (AMI) patients (n = 40) and healthy individuals (n = 30) (both p < 0.01) and positively correlated with CRP, IL-17, and IL-4 (all p < 0.01). Elevation of serum PDPN discriminated VMC from AMI (OR = 4.061, p < 0.01) and PDPN addition to the basic model (age, CRP, and peak cTNI) increased AUC values (from 0.822 to 0.933, p = 0.04). Additionally, the serum levels of PDPN ligand CCL-21 were also increased and correlated with PDPN (R = 0.59, p < 0.01) in VMC patients, accompanied by AHA production. Moreover, the anti-MHC antibody was closely related to PDPN levels (R = 0.53, p < 0.01), and anti-MHC-positive patients with VMC displayed higher percentages of CD4+IL-17A+PDPN+T cells and CD19+CCR7+B cells (both p < 0.05). Noticeably, VMC patients complicated by ventricular arrhythmias (27.50%) presented with AHA production and higher PDPN levels (p < 0.05). Finally, we screened out and verified that miR-182-5p directly targeted PDPN and negatively regulated its expression (all p < 0.01). These data suggested that blood PDPN might be a novel inflammation-associated biomarker for the early diagnosis of VMC and may contribute to AHA production by binding CCL-21 to recruit Th17 and B cells, which were regulated by miR-182-5p.

Cobalt Ferrite-Gossypol Coordination Nanoagents with High Photothermal Conversion Efficiency Sensitizing Chemotherapy against Bcl-2 to Induce Tumor Apoptosis.

Gossypol is a chemotherapeutic drug that can inhibit the anti-apoptotic protein Bcl-2, but the existing gossypol-related nanocarriers cannot well solve the problem of chemotherapy resistance. Based on the observation that gossypol becomes black upon Fe3+ coordination, it is hypothesized that encasing gossypol in glyceryl monooleate (GMO) and making it coordinate cobalt ferrite will not only improve its photothermal conversion efficiency (PCE) but also help it enter tumor cells. As the drug loading content and drug encapsulation efficiency of gossypol are 10.67% (w/w) and 96.20%, the PCE of cobalt ferrite rises from 14.71% to 36.00%. The synergistic therapeutic effect finally induces tumor apoptosis with a tumor inhibition rate of 96.56%, which is 2.99 and 1.47 times higher than chemotherapy or photothermal therapy (PTT) alone. PTT generated by the GMO nanocarriers under the irradiation of 808 nm laser can weaken tumor hypoxia, thereby assisting gossypol to inhibit Bcl-2. In addition, the efficacy of nanocarriers is also evaluated through T2 -weighted magnetic resonance imaging. Observations of gossypol-induced apoptosis in tissue slices provide definitive proof of chemotherapy sensitization, indicating that such coordination nanocarriers can be used as an effective preclinical agent to enhance chemotherapy.

Application of Machine Learning Technology in the Prediction of ADME- Related Pharmacokinetic Parameters.

BACKGROUND: As an important determinant in drug discovery, the accurate analysis and acquisition of pharmacokinetic parameters are very important for the clinical application of drugs. At present, the research and development of new drugs mainly obtain their pharmacokinetic parameters through data analysis, physiological model construction and other methods, but the results are often quite different from the actual situation, needing more manpower and material resources. OBJECTIVE: We mainly discuss the application of machine learning technology in the prediction of pharmacokinetic parameters, which are mainly related to the quantitative study of drug absorption, distribution, metabolism and excretion in the human body, such as bioavailability, clearance, apparent volume of distribution and so on. METHODS: This paper first introduces the pharmacokinetic parameters, the relationship between the quantitative structure-activity relationship model and machine learning, then discusses the application of machine learning technology in different prediction models, and finally discusses the limitations, prospects and future development of the machine learning model in predicting pharmacokinetic parameters. RESULTS: Unlike traditional pharmacokinetic analysis, machine learning technology can use computers and algorithms to speed up the acquisition of pharmacokinetic parameters to varying degrees. It provides a new idea to speed up and shorten the cycle of drug development, and has been successfully applied in drug design and development. CONCLUSION: The use of machine learning technology has great potential in predicting pharmacokinetic parameters. It also provides more choices and opportunities for the design and development of clinical drugs in the future.

SGLT2 inhibitor, canagliflozin, ameliorates cardiac inflammation in experimental autoimmune myocarditis.

Myocarditis is an inflammatory cardiovascular disease which contributes to dilated cardiomyopathy (DCM) and heart failure. Canagliflozin (CANA) exerts anti-inflammatory and cardioprotective effects in heart failure besides its hypoglycemic effect. However, the role of CANA in myocarditis has not been elucidated. In this work, CANA treatment markedly alleviated cardiac inflammation and improved cardiac function in experimental autoimmune myocarditis (EAM) mice induced by α-myosin-heavy chain peptides. The expressions of NLRP3 inflammasome complexes (NLRP3, ASC, and Caspase-1) and their downstream molecules (IL-1ß, IL-18) were significantly downregulated by CANA, accompanied with reduced Th17 cell infiltration in hearts. Furthermore, Bax/Bcl-2 ratio, Cleaved Caspase-3 protein level and the percentage of TUNEL-positive myocardial cells, which usually indicated apoptosis, were reduced by CANA treatment. These findings suggest CANA could be a valuable medication for myocarditis treatment.

The Potential of Metabolism-Related Gene OGDHL as a Biomarker for Myocardial Remodeling in Dilated Cardiomyopathy.

The development of dilated cardiomyopathy (DCM) is accompanied by a series of metabolic disorders, resulting in myocardial remodeling or exacerbation, while the mechanism remains not completely clear. This study was to find out the key metabolism-related genes involved in the onset of DCM, providing new insight into the pathogenesis of this disease. The datasets of GSE57338, GSE116250, and GSE5406 associated with hearts of patients with DCM were downloaded from the Gene Expression Omnibus database. GSE57338 was analyzed to screen out metabolism-related differentially expressed genes (DEGs), while GSE116250 and GSE5406 were utilized to verify the optimal genes through R software. Support vector machine recursive feature elimination algorithm and least absolute shrinkage and selection operator algorithm were used to determine key genes. Finally, 6 of 39 metabolism-related DEGs were screened out and identified as the optimal genes. After quantitative reverse-transcription polymerase chain reaction (qRT-PCR) validation performed on the samples drawn from the left ventricles of human hearts, it showed that only the expression of oxoglutarate dehydrogenase-like (OGDHL) increased while PLA2G2 decreased significantly in patients with DCM compared with non-failing donors, respectively. Furthermore, the higher OGDHL protein expression, except the change of PLA2G2, was also found in DCM hearts, and its mRNA expression was negatively correlated with myocardial Masson's scores (r = -0.84, P = 0.009) and left ventricular end-diastolic diameter (LVEDd; r = -0.82, P = 0.014), which might be regulated by miR-3925-5p through further bioinformatics prediction and qRT-PCR verification. The data then suggested that the metabolism-related gene OGDHL was associated with myocardial fibrosis of DCM and probably a biomarker for myocardial remodeling in patients with DCM.

[Effects of RPA1 down-regulation on the invasion and migration and cell cycle of human nasopharyngeal carcinoma CNE-2R cells with radio resistance].

Objective: To investigate the effects of RPA1 silencing on the invasion, migration and cell cycle of human nasopharyngeal carcinoma CNE-2R cells. Methods: shRNA technology was used to construct CNE-2R cell lines with RPA1 low-expression, which were verified by RT-PCR and Western blotting. The following assays were performed using the three 3 groups: control group(CNE-2),negative control group(NC-shRNA) and RPA1 down-regulation group(RPA1-shRNA). The effects of RPA silence on the proliferation, invasion, migration, and cell cycle of CNE-2R cells were detected using Cell Counting Kit-8, clone formation experiment, Transwell, scratch test and flow cytometry, respectively. The expressions of Chk2, p-Chk2, Cdc 25c and p-cdc25c were tested by Western blot assay. Results: The expressions of RPA1 mRNA and protein in the RPA1-shRNA group were lower than those in the CNE-2 and NC-shRNA groups significantly (P＜0.01 and 0.05). Compared with CNE-2 and NC-shRNA groups, the abilities of proliferation, invasion and migration of RPA1-shRNA group were decreased and the cell cycle in the RPA1-shRNA group was blocked in the G2/M phase (P＜0.01). The expressions of Chk2 and Cdc25c in RPA1-shRNA group cells were lower than those in CNE-2R and NC-shRNA group cells (P＜0.05), while the expressions of p-Chk2 and p-cdc25c were higher than those in the other groups (P＜0.05). Conclusion: After RPA1 silenced, the proliferation and migration of radio resistant human nasopharyngeal carcinoma CNE-2R cells was inhibited, resulting in cell cycle arrested in the G2/M phase.

Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension.

Despite the multiple diagnostic and therapeutic strategies implemented in clinical practice, the mortality rate of patients with pulmonary arterial hypertension (PAH) remains high. Understanding the mechanisms and key genes involved could provide insight into the drivers of the pathogenesis of PAH. In this research, we aimed to examine the mechanisms underlying PAH and identify key genes with potential usefulness as clinical biomarkers of PAH and thereby establish therapeutic targets for PAH. The datasets GSE117261, GSE113439, and GSE53408 were downloaded from the Gene Expression Omnibus (GEOs) database. We used weighted gene coexpression network analysis (WGCNA) to identify networks and the most relevant modules in PAH. Functional enrichment analysis was performed for the selected clinically relevant modules. The least absolute shrinkage and selection operator (LASSO) was applied to identify key genes in lung samples from patients with PAH. The genes were validated in a monocrotaline-induced PAH rat model. Three clinically relevant modules were identified through average linkage hierarchical clustering. The genes in the clinically relevant modules were related to endothelial cell differentiation, inflammation, and autoimmunity. Seven genes were screened as key genes significantly associated with PAH. Interferon-induced protein 44-like (IFI44L) and signal transducer and activator of transcription 1 (STAT1) were expressed at higher levels in the lung tissues of the PAH rat model than in those of the controls. Our findings reveal the novel pathological mechanisms underlying PAH and indicate that STAT1 and IFI44L may represent potential therapeutic targets in PAH.