Development and validation of a nomogram for predicting mortality in patients with acute severe traumatic brain injury: A retrospective analysis.

BACKGROUND: Recent evidence links the prognosis of traumatic brain injury (TBI) to various factors, including baseline clinical characteristics, TBI specifics, and neuroimaging outcomes. This study focuses on identifying risk factors for short-term survival in severe traumatic brain injury (sTBI) cases and developing a prognostic model. METHODS: Analyzing 430 acute sTBI patients from January 2018 to December 2023 at the 904th Hospital's Neurosurgery Department, this retrospective case-control study separated patients into survival outcomes: 288 deceased and 142 survivors. It evaluated baseline, clinical, hematological, and radiological data to identify risk and protective factors through univariate and Lasso regression. A multivariate model was then formulated to pinpoint independent prognostic factors, assessing their relationships via Spearman's correlation. The model's accuracy was gauged using the Receiver Operating Characteristic (ROC) curve, with additional statistical analyses for quantitative factors and model effectiveness. Internal validation employed ROC, calibration curves, Decision Curve Analysis (DCA), and Clinical Impact Curves (CIC) to assess model discrimination, utility, and accuracy. The International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) and Corticosteroid Randomization After Significant Head injury (CRASH) models were also compared through multivariate regression. RESULTS: Factors like unilateral and bilateral pupillary non-reactivity at admission, the derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR), D-dimer to fibrinogen ratio (DFR), infratentorial hematoma, and Helsinki CT score were identified as independent risk factors (OR > 1), whereas serum albumin emerged as a protective factor (OR < 1). The model showed superior predictive performance with an AUC of 0.955 and surpassed both IMPACT and CRASH models in predictive accuracy. Internal validation confirmed the model's high discriminative capability, clinical relevance, and effectiveness. CONCLUSIONS: Short-term survival in sTBI is significantly influenced by factors such as pupillary response, dNLR, PLR, DFR, serum albumin levels, infratentorial hematoma occurrence, and Helsinki CT scores at admission. The developed nomogram accurately predicts sTBI outcomes, offering significant clinical utility.

The value of D-dimer to lymphocyte ratio in predicting clinical outcomes after percutaneous coronary intervention in ST-segment elevation myocardial infarction patients: A retrospective study.

BACKGROUND: D-dimer to lymphocyte ratio (DLR) is a novel composite metric. This study investigated the association between DLR and major adverse cardiovascular events (MACEs) in patients with ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention. MATERIALS AND METHODS: This retrospective study included 683 STEMI cases treated between January 2018 and June 2021 at a single center. DLR was calculated for each patient. Receiver operating characteristic curves assessed the predictive value of in-hospital and long-term MACEs, with calculated AUC. Based on the optimal DLR cutoff value, the population was categorized into groups for clinical characteristic analysis. Multivariate logistic and COX regression analyses determined factors independently associated with MACEs. Kaplan-Meier estimation method and log-rank tests assessed event-free survival among different DLR groups. Spearman's test explored the correlation between DLR and Gensini score. RESULTS: DLR demonstrated an AUC of 0.792 for predicting in-hospital MACEs and 0.708 for long-term MACEs in patients with STEMI. Multivariate logistic regression analysis revealed that a high DLR (cutoff value, 0.47) independently increased the risk of MACEs during hospitalization in patients with STEMI (P = 0.003; odds ratio: 3.015; 95 % CI: 1.438-6.321). Multivariate COX regression showed that a high DLR (cutoff value, 0.34) independently predicted MACEs during long-term follow-up in patients with STEMI (P = 0.011; hazard ratio: 1.724; 95 % CI: 1.135-2.619). Furthermore, DLR exhibited a positive correlation with the Gensini score (P < 0.001). CONCLUSIONS: DLR is a valuable predictor for MACEs occurrence in patients with STEMI during hospitalization and long-term follow-up after PCI.

Relationship between the lymphocyte to C­reactive protein ratio and coronary artery disease severity.

Coronary atherosclerosis is a chronic systemic inflammatory disease. Laboratory parameters such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune inflammation index (SII) have been used to assess inflammation degree and coronary artery disease (CAD) severity. The lymphocyte-to-C-reactive protein ratio (LCR) is a new SII. However, its relationship with CAD development and severity is unclear. A total of 1,107 patients (479 in control group, 628 in CAD group) underwent coronary angiography. The routine and biochemical indices of the venous blood of patients were assessed before coronary angiography. LCR, SII, NLR and PLR were calculated and statistical analyses were performed. Propensity score matching (PSM) and a logistic regression model were used to analyze the relationship between LCR and CAD. After the PSM, 384 pairs of patients with or without CAD were successfully matched. After the median binary classification of all indicators, uni- and multivariate logistic regression analyses showed that platelet count was an independent risk factor and LCR was an independent protective factor. Using the same method, in the coronary heart disease severity group, 212 pairs were successfully matched and NLR and PLR were independent risk factors, while LCR was an independent protective factor. In conclusion, LCR is an independent protective factor against CAD development and severity.

Slow-Reflow and Prognosis in Patients with High Parathyroid Hormone Levels Undergoing Primary Percutaneous Coronary Intervention for Acute ST-Segment Elevation Myocardial Infarction.

We aimed to evaluate the correlation among serum parathyroid hormone (PTH) and slow-reflow during primary percutaneous coronary intervention (PCI) and prognosis in patients with ST-segment elevation myocardial infarction (STEMI). A total of 262 patients were enrolled and divided into a slow-reflow group (n = 61) and a control group (n = 201). PTH was an independent risk factor for slow-reflow (P < 0.05), and the regression model had good discrimination and calibration. ROC curve analysis showed that PTH (≥ 63.65 pg/ml) had a predictive value for slow-reflow (P < 0.001). During the 1-year follow-up, the patients were divided into a PTH-h group (≥ 63.65 pg/ml, n = 100) and a PTH-l group (< 63.65 pg/ml, n = 162). Readmission for HF was independently associated with PTH levels (P < 0.05). KM survival analysis suggested that PTH-h had a predictive value for MACEs, especially for readmission for HF (P < 0.05). PTH levels were associated with slow-reflow during PCI and MACEs during follow-up in patients with STEMI.

A fine recognition method of strawberry ripeness combining Mask R-CNN and region segmentation.

As a fruit with high economic value, strawberry has a short ripeness period, and harvesting at an incorrect time will seriously affect the quality of strawberries, thereby reducing economic benefits. Therefore, the timing of its harvesting is very demanding. A fine ripeness recognition can provide more accurate crop information, and guide strawberry harvest management more timely and effectively. This study proposes a fine recognition method for field strawberry ripeness that combines deep learning and image processing. The method is divided into three stages: In the first stage, self-calibrated convolutions are added to the Mask R-CNN backbone network to improve the model performance, and then the model is used to extract the strawberry target in the image. In the second stage, the strawberry target is divided into four sub-regions by region segmentation method, and the color feature values of B, G, L, a and S channels are extracted for each sub-region. In the third stage, the strawberry ripeness is classified according to the color feature values and the results are visualized. Experimental results show that with the incorporation of self-calibrated convolutions into the Mask R-CNN, the model's performance has been substantially enhanced, leading to increased robustness against diverse occlusion interferences. As a result, the final average precision (AP) has improved to 0.937, representing a significant increase of 0.039 compared to the previous version. The strawberry ripeness classification effect is the best on the SVM classifier, and the accuracy under the combined channel BGLaS reaches 0.866. The classification results are better than common manual feature extraction methods and AlexNet, ResNet18 models. In order to clarify the role of the region segmentation method, the contribution of different sub-regions to each ripeness is also explored. The comprehensive results demonstrate that the proposed method enables the evaluation of six distinct ripeness levels of strawberries in the complex field environment. This method can provide accurate decision support for strawberry refined planting management.

Association of Systemic Inflammatory Response Index and Pan-Immune-Inflammation-Value with Long-Term Adverse Cardiovascular Events in ST-Segment Elevation Myocardial Infarction Patients After Primary Percutaneous Coronary Intervention.

Aim: Reducing the high morbidity and mortality of ST-segment elevation myocardial infarction (STEMI) and improving patient prognosis remains a major global challenge. This study aimed to explore whether dynamic fluctuations in biomarkers are valuable predictors of prognosis in patients with STEMI. Methods: This study included 216 patients with STEMI. Blood routine tests were performed on admission, 12 h after percutaneous coronary intervention (PCI), and at discharge. Systemic immune-inflammation index (SII), systemic inflammatory response index (SIRI), and pan-immune-inflammation-value (PIV) serum immune-inflammatory markers were calculated. The Cox proportional hazard model was used to assess the factors independently associated with the prognosis of STEMI. The optimal cutoff values for the inflammatory markers were calculated. Results: Eighty-five (39.35%) of the 216 patients had major adverse cardiovascular events (MACEs) during the 1-year follow-up. Most were male (81.18%) with a median age of 64 years (interquartile, 55-69.5). Killip class ≥ II on admission (hazard ratio [HR], 1.859; 95% CI, 1.169-2.957; P = 0.009), total stent length (HR, 1.016; 95% CI, 1.003-1.029; P = 0.019), values of SIRI at 12 h after PCI (HR, 1.079; 95% CI, 1.050-1.108; P < 0.001), and the Gensini score (HR, 1.014; 95% CI, 1.007-1.022; P < 0.001) were independently associated with an increased risk of MACEs. Compared with SII, SIRI and PIV calculated at various time points and dynamically fluctuating changes, SIRI (cutoff value, 4.15; 95% CI, 0.701-0.819; P < 0.001) and PIV (cutoff value, 622.71; 95% CI, 0.674-0.796; P < 0.001) at 12 h after PCI showed the best efficacy for the prognosis of STEMI. Conclusion: Our study provides relevant evidence to the notion that SIRI or PIV at 12 h after PCI may be more accurate and economical predictors of long-term adverse prognosis in patients with STEMI.

Construction of Core-Cross-Linked Polymer Micelles with High Biocompatibility and Stability for pH/Reduction Controllable Drug Delivery.

Polymer micelles have been studied extensively in drug delivery systems (DDS), and their stability is well known to directly affect drug delivery. In this article, a series of amphiphilic copolymers LA-PDPAn-PVPm were synthesized to prepare core-cross-linked nanoparticles (CNP) applied to controllable and targeted anticancer drug delivery. The copolymers could self-assemble in aqueous solution and form homogeneous spherical micelles with particle sizes of between 100 and 150 nm. A comparison between un-cross-linked UCNP and CNP showed that the cross-linking of LA could significantly improve the stability and responsive ability of the nanoparticles. From the in vitro-simulated drug release experiments, CNP was found to have great drug blocking ability under normal physiological conditions and could achieve rapid and efficient drug release under acidic/reducing conditions. In addition, cell experiments showed that CNP had superior biocompatibility and could target tumor cells for drug release. In conclusion, a drug carrier based on copolymer LA-PDPA-PVP realized effective controlled drug release due to the cross-linking of LA. The results will provide guidance for the design strategy of polymer micelles for drug carriers.

Corrigendum: A nomogram risk prediction model for no-reflow after primary percutaneous coronary intervention based on rapidly accessible patient data among patients with ST-segment elevation myocardial infarction and its relationship with prognosis.

[This corrects the article DOI: 10.3389/fcvm.2022.966299.].

Prognostic role of tissue plasminogen activator in coronary artery disease with or without aortic valve sclerosis.

AIMS: We sought to investigate the relationship between circulating tissue plasminogen activator (t-PA) level and long-term outcomes in stable coronary artery disease patients with or without aortic valve sclerosis (AVSc). METHODS AND RESULTS: Serum levels of t-PA were determined in 347 consecutive stable angina patients with (n = 183) or without (n = 164) AVSc. Outcomes were prospectively recorded as planned clinic evaluations every 6 months up to 7 years. The primary endpoint was a composite of cardiovascular death and rehospitalization due to heart failure. The secondary endpoint included all-cause mortality, cardiovascular death, and rehospitalization due to heart failure. Serum t-PA was significantly higher in AVSc than in non-AVSc patients (2131.22 pg/mL vs. 1495.85 pg/mL, P < 0.001). For patients with AVSc, those with t-PA level above the median (>1840.68 pg/mL) were more likely to meet the primary and secondary endpoints (all P < 0.001). After adjusting for potential confounding factors, serum t-PA level remained significantly predictive for each endpoint in the Cox proportional hazard models. The prognostic value of t-PA was good, with an AUC-ROC of 0.753 (P < 0.001). The combination of t-PA with traditional risk factors improved the risk reclassification of AVSc patients, with a net reclassification index of 0.857 and an integrated discrimination improvement of 0.217 (all P < 0.001). However, for patients without AVSc, both primary and secondary endpoints were similar, irrespective of t-PA levels. CONCLUSIONS: Elevated circulating t-PA confers an increased risk for poor long-term clinical outcomes in stable coronary artery disease patients with AVSc.

Correlation Between GDF11 Serum Levels, Severity of Coronary Artery Lesions, and the Prognosis of Patients with ST-segment Elevation Myocardial Infarction.

We aimed to explore the correlation among serum GDF11, the severity of coronary artery lesions, and the prognosis of patients with ST-segment elevation myocardial infarction (STEMI). A total of 367 patients were enrolled and divided into control (n = 172) and STEMI (n = 195) groups. Serum GDF11 (P < 0.001) was an independent predictor of STEMI and was negatively correlated with SYNTAX score (P < 0.05). ROC curve analysis showed that serum GDF11 could screen patients for major adverse cardiovascular events (MACEs). KM curve analysis showed that patients with lower concentration of GDF11 had a higher incidence of MACEs, and Cox proportional hazards regression analysis showed that the serum GDF11 (P < 0.001) was an independent predictor of MACEs. Serum GDF11 was negatively correlated with the severity of coronary lesions and was also an independent prognostic indicator of MACEs in patients with STEMI.

Human Nanoplatelets as Living Vehicles for Tumor-Targeted Endocytosis In Vitro and Imaging In Vivo.

Recent studies have shown human platelets can access the tumor microenvironment by passive diffusion across capillaries or via activated immune cells. In a previous study, we exploited this affinity of platelets for tumor cells as part of a new approach to target tumors with modified platelets. Therefore, the engineering of human nanoplatelets as living vehicles for in vivo tumor-targeted near-infra-red fluorescence (NIRF) imaging and the delivery of cytotoxins to tumor cells by endocytosis are described in this study. Nanoplatelets with an average diameter of 200 nm were prepared by mild sonication of kabiramide C (KabC)-loaded human platelets. The sealed plasma membrane of the nanoplatelets allows them to accumulate and retain membrane-permeable chemicals, such as epidoxorubicin (EPI) and KabC. Tumor-targeted imaging functionalities were engineered on the nanoplatelets by surface-coupling transferrin, Cy5 and Cy7. High-resolution fluorescence imaging and flow cytometry analyses showed that the nanoplatelets loaded with EPI and Cy5 targeted human myeloma cells (RPMI8226 cells) that over-expressed the transferrin receptor. The endocytosis of the nanoplatelets by RPMI8226 cells was transferrin-dependent and induced apoptosis. The test results also showed that the nanoplatelets functionalized with transferrin and Cy7 and injected in mice bearing RPMI8226 cells-derived myeloma xenotransplants accumulated in the tumor tissue and could be used for high-contrast in vivo NIRF imaging of early-stage tumors. Nanoplatelets represent a new class of living nano-vehicles that may efficiently target and deliver therapeutic agents and imaging probes to diseased tissues including tumors.

Preoperative lymphocyte to C-reactive protein ratio: A new prognostic indicator of post-primary percutaneous coronary intervention in patients with ST-segment elevation myocardial infarction.

BACKGROUND: The lymphocyte-to-C-reactive protein ratio (LCR) is a novel inflammatory biomarker for many diseases. This study aimed to examine the association between LCR and major adverse cardiovascular events (MACEs) in patients with ST-segment elevation myocardial infarction (STEMI) who were undergoing percutaneous coronary intervention. METHODS: A total of 382 patients with STEMI were included in this study; these patients were enrolled from January 2014 to January 2016 at a single center, and the LCR was calculated for each patient. During the in-hospital and long-term follow-up period, MACEs included cardiovascular death, new-onset non-fatal myocardial infarction, heart failure, malignant arrhythmias, revascularization in unstable angina, and new-onset atrial fibrillation. Using receiver operating characteristic curves, we assessed the predictive impact for MACEs using a combination of six inflammatory markers in patients with STEMI and focused on LCR to elucidate its prognostic value. Univariate and multivariate Cox proportional hazard models were used to define the factors associated with MACEs. RESULTS: Among the assessed variables, preoperative LCR showed the highest accuracy in predicting hospitalized (AUC:0.71) and long-term follow-up(AUC:0.602) MACEs in patients with STEMI. Decreased preoperative LCR was significantly associated with the Gensini score (P < 0.05) and no-reflow (P < 0.05). Multivariate Cox analysis showed that a high preoperative LCR (cutoff threshold = 112.4) was an independent protective factor for hospitalized MACEs in patients with STEMI (hazard ratio, 0.409; 95 % confidence interval, 0.283-0.590; P < 0.001). A high preoperative LCR (cutoff threshold = 106.3) was an independent protective factor for long-term follow-up MACEs in patients with STEMI (hazard ratio, 0.552; 95 % confidence interval, 0.369-0.740; P < 0.001). CONCLUSION: Preoperative LCR is a novel and valuable prognostic marker to determine the occurrence of MACEs in hospitals and long-term follow-up after primary percutaneous coronary intervention in patients with STEMI.

Identification of key genes involved in calcific aortic valve disease based on integrated bioinformatics analysis.

The calcific aortic valve disease (CAVD) develops as an aortic valve sclerosis and progresses to an advanced form of stenosis. In many biological fields, bioinformatics becomes a fundamental component. The key mechanisms involved in CAVD are discovered with the use of bioinformatics to investigate gene function and pathways. We downloaded the original data (GSE51472) from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). After standardization, 2978 differentially expressed genes (DEGs) were identified from the data sets GSE51472 containing samples from normal, calcified, and sclerotic aortic valves. Analysis of DEGs based on the series test of clusters (STCs) revealed the two most significant patterns. Based on the result of the STC, the functional enrichment analysis of gene ontology (GO) was conducted to investigate the molecular function (MF), biological process (BP), and cell compound (CC) of the DEGs. With a p value of 0.01, DEGs associated with "chronic inflammation," "T-cell receptor complexes," and "antigen binding" had the highest significance within BP, CC, and MF. DEG enrichment in signaling pathways was analyzed using KEGG pathway enrichment. Using a p < 0.05 level of significance, the most enriched biological pathways related to CAVD were "Chemokine signaling pathway," "Cytokine-cytokine receptor interaction," "Tuberculosis," "PI3K-Akt signaling pathway," and "Transcriptional misregulation in cancer." Finally, the construction of gene co-expression networks and pathway networks illustrated the pathogensis of CAVD. TLR2, CD86, and TYROBP were identified as hub genes for the development of CAVD. Moreover, "MAPK signaling pathway," "Apoptosis," and "Pathways in cancer" were regarded as the core pathways among the samples of normal, sclerotic and calcified aortic valve samples.

The relationship of serum gastrin-17 and oral mucositis in head and neck carcinoma patients receiving radiotherapy.

OBJECTIVE: The aim of this study was to analyze the relationship of serum gastrin-17 (G-17) and oral mucositis in head and neck carcinoma (HNC) patients receiving radiotherapy. METHODS: Serum G-17 were detected in patients before and after radiotherapy. Patients were divided into high G-17 group (baseline serum G-17 ≥ 5pmol/L) and low G-17 group (baseline serum G-17 < 5pmol/L). The severity of oral mucositis was analyzed between the two groups. Other complications such as dysphagia, salivary gland, mandible, thyroid function, larynx, pain, and weight loss were also investigated. RESULTS: Forty-two patients were analyzed in this study. The level of serum G-17 had a significant decrease after radiotherapy (7.29 ± 5.70pmol/L versus 4.93 ± 4.46pmol/L, P = 0.038). In low serum G-17 group, the incidences of grade 0, 1-2 and 3-4 of oral mucositis were 0%, 30.4%, and 69.6%, respectively. In high serum G-17 group, the incidences of grade 0, 1-2 and 3-4 of oral mucositis were 0%, 63.2%, and 36.8%, respectively. Pearson correlation analysis showed that serum G-17 was negatively correlated with oral mucositis (r=-0.595, P < 0.01). Weight loss of low G-17 group was more serious than that of high G-17 group. CONCLUSION: Serum G-17 has a close relationship with oral mucositis. Baseline serum G-17 may be a potential predictor for the severity of oral mucositis in HNC patients receiving radiotherapy.

GDF11 Is a Novel Protective Factor Against Vascular Calcification.

ABSTRACT: Vascular calcification (VC) occurs via an active cell-mediated process, which involves osteogenic differentiation, apoptosis, and phenotypic transformation of vascular smooth muscle cells (VSMCs). As a member of the transforming growth factor-ß family, growth differentiation factor 11 (GDF11) can inhibit apoptosis and osteogenic differentiation and maintain the stability of atherosclerotic plaques. In this study, coronary artery calcium score (CACS) of participants with GDF11 measurements was measured using computed tomography angiography and was scored according to the Agatston score. ß-glycerophosphate (10 mM), dexamethasone (100 nM), and l -ascorbic acid (50 µg/mL) [osteogenic medium (OM)] were used to induce calcification of human aortic smooth muscle cells. We found that CACS was negatively correlated with serum GDF11 levels in patients and GDF11 was a strong predictor of elevated CACS (OR = 0.967, 95% CI: 0.945-0.991; P = 0.006), followed by age (OR = 1.151, 95% CI: 1.029-1.286; P = 0.014), triglycerides (OR = 4.743, 95% CI: 1.170-19.236; P = 0.029), C-reactive protein (OR = 1.230, 95% CI: 1.010-1.498; P = 0.04), and hypertension (OR = 7.264, 95% CI: 1.099-48.002; P = 0.04). Furthermore, exogenous GDF11 inhibited OM-induced calcification by inhibiting osteogenic differentiation, the phenotypic transformation and apoptosis of human aortic smooth muscle cells. Our study demonstrates that GDF11 plays a crucial role in reducing vascular calcification and serves as a potential intervention target to vascular calcification.

A nomogram risk prediction model for no-reflow after primary percutaneous coronary intervention based on rapidly accessible patient data among patients with ST-segment elevation myocardial infarction and its relationship with prognosis.

Background: No-reflow occurring after primary percutaneous coronary intervention (PCI) in patients with ST-segment elevation myocardial infarction (STEMI) can increase the incidence of major adverse cardiovascular events (MACE). The present study aimed to construct a nomogram prediction model that can be quickly referred to before surgery to predict the risk for no-reflow after PCI in STEMI patients, and to further explore its prognostic utility in this patient population. Methods: Research subjects included 443 STEMI patients who underwent primary PCI between February 2018 and February 2021. Rapidly available clinical data obtained from emergency admissions were collected. Independent risk factors for no-reflow were analyzed using a multivariate logistic regression model. Subsequently, a nomogram for no-reflow was constructed and verified using bootstrap resampling. A receiver operating characteristic (ROC) curve was plotted to evaluate the discrimination ability of the nomogram model and a calibration curve was used to assess the concentricity between the model probability curve and ideal curve. Finally, the clinical utility of the model was evaluated using decision curve analysis. Results: The incidence of no-reflow was 18% among patients with STEMI. Killip class ≥2 on admission, pre-operative D-dimer and fibrinogen levels, and systemic immune-inflammation index (SII) were independent risk factors for no-reflow. A simple and quickly accessible prediction nomogram for no-reflow after PCI was developed. This nomogram demonstrated good discrimination, with an area under the ROC curve of 0.716. This nomogram was further validated using bootstrapping with 1,000 repetitions; the C-index of the bootstrap model was 0.706. Decision curve analysis revealed that this model demonstrated good fit and calibration and positive net benefits. Kaplan-Meier survival curve analysis revealed that patients with higher model scores were at a higher risk of MACE. Multivariate Cox regression analysis revealed that higher model score(s) was an independent predictor of MACE (hazard ratio 2.062; P = 0.004). Conclusions: A nomogram prediction model that can be quickly referred to before surgery to predict the risk for no-reflow after PCI in STEMI patients was constructed. This novel nomogram may be useful in identifying STEMI patients at higher risk for no-reflow and may predict prognosis in this patient population.

Construction of pH/reduction dual responsive MSN-HAgel containing HApt for tumor targeting carriers.

In this study, a pH/reduction dual responsive carrier containing 42nt-nucleic acid HApt based on mesoporous silica nanoparticles (MSNs) was designed. Two kinds of low molecular weight oligomeric hyaluronic acid (HA) were used to graft onto MSN for better drug encapsulation. Crosslinked MSN-HA3000gel and MSN-HA11000gel were prepared by crosslinking the HA chain through the sulfhydrylization of the carboxyl group on the HA side chain. An appropriate amount of sulfhydryl nucleic acid (HApt-SH) was added during the crosslinking reaction, which realized the targeting ability and apoptosis function to cancer cells overexpressing the HER2 receptor. Crosslinked HA had a good effect on decreasing the side effect of DOX that the drug leakage was less than 20% under a normal body environment. However, it could realize rapid and efficient drug release in a tumor environment. As to the release of HApt, it exhibited a good response to GSH. The cytotoxicity test showed that HApt contained in HAgel had a great targeting effect and significant cytotoxicity to SKBR3 cells. As a whole, this MSN-HAgel enabled the combination of gene therapy and chemotherapy, showing the synergistic effect of "1 + 1 > 2", providing a novel idea for cancer treatments.

CircSamd4: A novel biomarker for predicting vascular calcification.

BACKGROUND: Vascular calcification (VC) is usually associated with cardiovascular diseases (CVDs), which are one of the main causes of mortality in the world. This study aimed to analyze the expression of circular RNAs (circRNAs) in patients with VC and to evaluate biomarkers for the diagnosis of VC. METHODS: Calcified human aortic endothelial cells (HAECs) and the calcification in mouse aorta were detected by qRT-PCR. Subsequently, this was verified in the plasma of patients with coronary artery calcification (CAC). The plasma of 40 patients in the control group and 31 patients in the calcified group were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR) to detect the level of circSamd4a in the blood. The diagnostic value was evaluated by logistic regression analysis and the working characteristics of subjects. RESULTS: In the HAECs, the qRT-PCR showed a significant decrease in the level of circSamd4a expression in the calcification group compared to the control group (p < 0.05). The calcified mouse aorta showed the same trend for circSamd4a expression, wherein the difference was statistically significant (p < 0.05); the expression of circSamd4a was significantly downregulated in the plasma of patients with VC (p < 0.01). The receiver operating characteristic (ROC) curves of circSamd4a in patients with VC and control group showed that the area under the curve (AUC) was 0.81 (95% CI: 0.707-0.913; p < 0.001). CONCLUSION: CircSamd4a showed a stable downward trend in different specimens, and had significant advantages as a biomarker for diagnosis of VC.

[Knockdown of PCSK9 inhibits endothelial-to-mesenchymal transition of human aortic endothelial cells].

Objective To investigate the protective effect of proprotein convertase subtilisin/kexin type 9 (PCSK9) knockdown on endothelial-to-mesenchymal transition (EndoMT) induced by ß glycerophosphate, dexamethasone, and L-ascorbic acid in human aortic endothelial cells (HAECs). Methods EndoMT model was established by inducing HAECs with (0, 10, 30, 50) mmol/L of ß glycerophosphate combined with 100 nmol/L of dexamethasone and 50 µg/mL of L-ascorbic acid. HAECs were transfected with specific small interfering RNA of PCSK9 (si-PCSK9), and the mRNA and protein expression levels of PCSK9 in HAECs were detected by real-time quantitative PCR and Western blotting. HAECs were randomized into blank group, EndoMT group, EndoMT group transfected with negative control small interfering RNA (si-NC), and EndoMT group transfected with si-PCSK9. The mRNA levels of α-smooth muscle actin (α-SMA), fibroblast-specific protein 1 (FSP1), and vascular endothelial cadherin (VE-cadherin) were detected by real-time quantitative PCR, the protein levels of α-SMA and VE-cadherin were detected by Western blotting, and the expression of α-SMA was detected by immunofluorescence staining. Results 30 mmol/L of ß glycerophosphate had the best effect in inducing EndoMT, and the expression of PCSK9 mRNA and protein was up-regulated when EndoMT occurred. After PCSK9 knockdown, the expressions of α-SMA and FSP1 were down-regulated, while the expression of VE cadherin was up-regulated. Conclusion Knockdown of PCSK9 inhibits the EndoMT of HAECs.