Aortic remodeling of the provisional extension to induce complete attachment technique in DeBakey type IIIb aortic dissection.

BACKGROUND/PURPOSE: Data about volumetric remodeling of the provisional extension to induce complete attachment (PETTICOAT) technique on DeBakey type IIIb aortic dissection in acute and subacute phases were scarce. The proper timing to perform this technique to promote false lumen reduction was also unknown. METHODS: Patients with DeBakey type IIIb aortic dissection who underwent the PETTICOAT technique between December 2005 and March 2017 were reviewed and divided into acute (treatment occurred ≦14 days after symptom onset) and subacute (15-90 days) groups. Remodeling parameters of the true and false lumens were analyzed. Receiver operating characteristic curve was used to deduce the timing of this technique. RESULTS: In the 2-year follow-up, the acute group (N = 20) demonstrated significant true lumen expansion and false lumen regression in the thoracic, abdominal, and total aorta. However, the subacute group (N = 20) only showed significant shrinkage in the false lumen of the thoracic and total aorta. Using PETTICOAT technique within 36 days after the aortic event may result in better total false lumen reduction. CONCLUSION: For DeBakey type IIIb aortic dissection, more prominent true lumen expansion and false lumen reduction were noted when using the PETTICOAT technique in the acute phase. When performed within 36 days after symptoms onset, the PETTICOAT technique may potentiate better total false lumen regression.

Correction: Lu et al. Periodontal Pathogen Adhesion, Cytotoxicity, and Surface Free Energy of Different Materials for an Implant Prosthesis Screw Access Hole. Medicina 2022, 58, 329.

In the original publication [...].

Periodontal Pathogen Adhesion, Cytotoxicity, and Surface Free Energy of Different Materials for an Implant Prosthesis Screw Access Hole.

Background and Objectives: Oral implant restorations are an excellent treatment option for edentulous patients; however, periodontopathogenic bacteria have been found in the microgaps between implant-abutment junctions. Implant designs to limit the microgaps have been extensively studied. However, studies have shown microgaps continue to exist, allowing for the leakage of bacteria into the implant system. Screw access hole materials are used to fill the access hole void. The use of materials with beneficial properties could provide bacterial leakage prevention. The aim of this study was to examine the surface free energy, cytotoxicity, and bacterial adhesion of selected screw access hole materials such as cotton, polytetrafluoroethylene (PTFE) tape, paraffin wax-polyolefin thermoplastic (PF), paraffin wax (Wax), gutta-percha (GP), and caviton EX (CE). Materials and Methods: A sessile drop test was performed to observe the contact angle and calculate the surface free energy of each material in order to determine the level of hydrophobicity. Cytotoxicity was examined in a mouse gingival epithelial cell line for day 1 and day 3. Bacterial adhesion was tested with Porphyromonas gingivalis, Fusobacterium nucleatum, and Aggregatibacter actinomycetemcomitans. Results: PTFE, PF, and wax presented low surface free energies of 19.34, 23.041, and 24.883 mN.m-1, respectively. No cytotoxicity was observed, except for GP and CE. Concurrently, the bacterial adhesion was also the lowest in PTFE and PF. Conclusions: Within the limits of this study, PTFE and PF showed an excellent biocompatibility with few bacterial adhesions. These materials could be potential screw access hole materials in clinical settings.

Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.

OBJECTIVE: To develop and evaluate the performance of U-Net for fully automated localization and segmentation of cervical tumors in magnetic resonance (MR) images and the robustness of extracting apparent diffusion coefficient (ADC) radiomics features. METHODS: This retrospective study involved analysis of MR images from 169 patients with cervical cancer stage IB-IVA captured; among them, diffusion-weighted (DW) images from 144 patients were used for training, and another 25 patients were recruited for testing. A U-Net convolutional network was developed to perform automated tumor segmentation. The manually delineated tumor region was used as the ground truth for comparison. Segmentation performance was assessed for various combinations of input sources for training. ADC radiomics were extracted and assessed using Pearson correlation. The reproducibility of the training was also assessed. RESULTS: Combining b0, b1000, and ADC images as a triple-channel input exhibited the highest learning efficacy in the training phase and had the highest accuracy in the testing dataset, with a dice coefficient of 0.82, sensitivity 0.89, and a positive predicted value 0.92. The first-order ADC radiomics parameters were significantly correlated between the manually contoured and fully automated segmentation methods (p < 0.05). Reproducibility between the first and second training iterations was high for the first-order radiomics parameters (intraclass correlation coefficient = 0.70-0.99). CONCLUSION: U-Net-based deep learning can perform accurate localization and segmentation of cervical cancer in DW MR images. First-order radiomics features extracted from whole tumor volume demonstrate the potential robustness for longitudinal monitoring of tumor responses in broad clinical settings. U-Net-based deep learning can perform accurate localization and segmentation of cervical cancer in DW MR images. KEY POINTS: • U-Net-based deep learning can perform accurate fully automated localization and segmentation of cervical cancer in diffusion-weighted MR images. • Combining b0, b1000, and apparent diffusion coefficient (ADC) images exhibited the highest accuracy in fully automated localization. • First-order radiomics feature extraction from whole tumor volume was robust and could thus potentially be used for longitudinal monitoring of treatment responses.

Galectin-3 Modulates Macrophage Activation and Contributes Smooth Muscle Cells Apoptosis in Abdominal Aortic Aneurysm Pathogenesis.

Galectin-3 (Gal-3) is a 26-kDa lectin that regulates many aspects of inflammatory cell behavior. We assessed the hypothesis that increased levels of Gal-3 contribute to abdominal aortic aneurysm (AAA) progression by enhancing monocyte chemoattraction through macrophage activation. We analyzed the plasma levels of Gal-3 in 76 patients with AAA (AAA group) and 97 controls (CTL group) as well as in angiotensin II (Ang-II)-infused ApoE knockout mice. Additionally, conditioned media (CM) were used to polarize THP-1 monocyte to M1 macrophages with or without Gal-3 inhibition through small interfering RNA targeted deletion to investigate whether Gal-3 inhibition could attenuate macrophage-induced inflammation and smooth muscle cell (SMC) apoptosis. Our results showed a markedly increased expression of Gal-3 in the plasma and aorta in the AAA patients and experimental mice compared with the CTL group. An in vitro study demonstrated that the M1 cells exhibited increased Gal-3 expression. Gal-3 inhibition markedly decreased the quantity of macrophage-induced inflammatory regulators, including IL-8, TNF-α, and IL-1ß, as well as messenger RNA expression and MMP-9 activity. Moreover, Gal-3-deficient CM weakened SMC apoptosis through Fas activation. These findings prove that Gal-3 may contribute to AAA progression by the activation of inflammatory macrophages, thereby promoting SMC apoptosis.

Metabolomic biomarkers in cervicovaginal fluid for detecting endometrial cancer through nuclear magnetic resonance spectroscopy.

INTRODUCTION: Endometrial cancer (EC) is one of the most common gynecologic neoplasms in developed countries but lacks screening biomarkers. OBJECTIVES: We aim to identify and validate metabolomic biomarkers in cervicovaginal fluid (CVF) for detecting EC through nuclear magnetic resonance (NMR) spectroscopy. METHODS: We screened 100 women with suspicion of EC and benign gynecological conditions, and randomized them into the training and independent testing datasets using a 5:1 study design. CVF samples were analyzed using a 600-MHz NMR spectrometer equipped with a cryoprobe. Four machine learning algorithms-support vector machine (SVM), partial least squares discriminant analysis (PLS-DA), random forest (RF), and logistic regression (LR), were applied to develop the model for identifying metabolomic biomarkers in cervicovaginal fluid for EC detection. RESULTS: A total of 54 women were eligible for the final analysis, with 21 EC and 33 non-EC. From 29 identified metabolites in cervicovaginal fluid samples, the top-ranking metabolites chosen through SVM, RF and PLS-DA which existed in independent metabolic pathways, i.e. phosphocholine, malate, and asparagine, were selected to build the prediction model. The SVM, PLS-DA, RF, and LR methods all yielded area under the curve values between 0.88 and 0.92 in the training dataset. In the testing dataset, the SVM and RF methods yielded the highest accuracy of 0.78 and the specificity of 0.75 and 0.80, respectively. CONCLUSION: Phosphocholine, asparagine, and malate from cervicovaginal fluid, which were identified and independently validated through models built using machine learning algorithms, are promising metabolomic biomarkers for the detection of EC using NMR spectroscopy.

Prognostic model based on magnetic resonance imaging, whole-tumour apparent diffusion coefficient values and HPV genotyping for stage IB-IV cervical cancer patients following chemoradiotherapy.

OBJECTIVES: To develop and validate a prognostic model of integrating whole-tumour apparent diffusion coefficient (ADC) from pretreatment diffusion-weighted (DW) magnetic resonance (MR) imaging with human papillomavirus (HPV) genotyping in predicting the overall survival (OS) and disease-free survival (DFS) for women with stage IB-IV cervical cancer following concurrent chemoradiotherapy (CCRT). METHODS: We retrospectively analysed three prospectively collected cohorts comprising 300 patients with stage IB-IV cervical cancer treated with CCRT in 2007-2014 and filtered 134 female patients who underwent MR imaging at 3.0 T for final analysis (age, 24-92 years; median, 54 years). Univariate and multivariate Cox regression analyses were used to evaluate the whole-tumour ADC histogram parameters, HPV genotyping and relevant clinical variables in predicting OS and DFS. The dataset was randomly split into training (n = 88) and testing (n = 46) datasets for construction and independent bootstrap validation of the models. RESULTS: The median follow-up time for surviving patients was 69 months (range, 9-126 months). Non-squamous cell type, ADC10 <0.77 × 10-3 mm2/s, T3-4, M1 stage and high-risk HPV status were selected to generate a model, in which the OS and DFS for the low, intermediate and high-risk groups were significantly stratified (p < 0.0001). The prognostic model improved the prediction significantly compared with the International Federation of Gynaecology and Obstetrics (FIGO) stage for both the training and independent testing datasets (p < 0.0001). CONCLUSIONS: The prognostic model based on integrated clinical and imaging data could be a useful clinical biomarker to predict OS and DFS in patients with stage IB-IV cervical cancer treated with CCRT. KEY POINTS: • ADC 10 is the best prognostic factor among ADC parameters in cervical cancer treated with CCRT • A novel prognostic model was built based on histology, ADC 10 , T and M stage and HPV status • The prognostic model outperforms FIGO stage in the survival prediction.

Developing and validating a multivariable prediction model to improve the diagnostic accuracy in determination of cervical versus endometrial origin of uterine adenocarcinomas: A prospective MR study combining diffusion-weighted imaging and spectroscopy.

BACKGROUND: A triage test to assist clinical decision-making on choosing primary chemoradiation for cervical carcinomas or primary surgery for endometrial carcinomas is important. PURPOSE OR HYPOTHESIS: To develop and validate a multiparametric prediction model based on MR imaging and spectroscopy in distinguishing adenocarcinomas of uterine cervical or endometrial origin. STUDY TYPE: Prospective diagnostic accuracy study. POPULATION: Eighty-seven women: 25 cervical and 62 endometrial adenocarcinomas divided into training (n = 43; cervical/endometrial adenocarcinomas = 11/32) and validation (n = 44; 14/30) datasets. FIELD STRENGTH/SEQUENCE: The 3T diffusion-weighted (DW) MR imaging and MR spectroscopy. ASSESSMENT: Morphology, volumetric DW MR imaging and spectroscopy (MDS) scoring system with total points 0-5, based on presence of the following MR features assessed independently by two radiologists: (a) epicenter at the cervix, (b) rim enhancement, (c) disrupted cervical stromal integrity, (d) mean volumetric apparent diffusion coefficient values (ADCmean) higher than 0.98 × 10-3 mm2 /s, (e) fatty acyl δ 1.3 ppm more than 161.92 mM. Histopathology as gold standard. STATISTICAL TESTS: Logistic regression and receiver operator characteristic (ROC) curves analysis. RESULTS: For both the training and validation datasets, the MDS score achieved an accuracy of 93.0% and 84.1%, significantly higher than that of morphology (88.4% and 79.5%), ADC value (74.4% and 68.2%), and spectroscopy (81.4% and 68.2%; P < 0.05 for all). The performances of the scoring were superior to the morphology in the training dataset (areas under the receiver operating characteristics curve [AUC] = 0.95 vs. 0.89; P = 0.046), but not in the validation dataset (AUC = 0.90 vs. 0.85; P = 0.289). DATA CONCLUSION: MDS score has potentials to improve distinguishing adenocarcinomas of cervical or endometrial origin, and warrants large-scale studies for further validation. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1654-1666.

A potential contribution of dipeptidyl peptidase-4 by the mediation of monocyte differentiation in the development and progression of abdominal aortic aneurysms.

OBJECTIVE: Abdominal aortic aneurysms (AAAs) are characterized by the destruction of elastin and collagen in the media and adventitia. Dipeptidyl peptidase-4 (DPP-4, an adipokine known as CD26) influences cell signaling, cell-matrix interactions, and the regulation of the functional activity of incretins in metabolic and inflammatory disorders. Although the role of DPP-4 in AAA evolution has been demonstrated, the underlying mechanisms of DPP-4-regulated AAA development remains unknown. METHODS: Patients with AAA (n = 93) and healthy controls (CTL, n = 20) were recruited. Based on computed tomography image analyses, 93 patients were divided into two groups: those with a small AAA (SAA, aortic diameter <5 cm, n = 16) and those with a large AAA (LAA, aortic diameter ≥5 cm, n = 77). Plasma DPP-4, glucagon-like peptide-1 levels, and expression of CD26 on mononuclear cells were analyzed. In addition, phorbol 12-myristate 13-acetate (PMA)-induced THP-1 cells and angiotensin II-infused apolipoprotein EtmlUnc mice were used to explore the underlying mechanisms. RESULTS: The levels of DPP-4 (µU/µg) increased while active glucagon-like peptide-1 (pM) decreased in patients with AAA in a diameter-dependent manner [CTL: 2.3 ± 1.5 and 3.7 ± 2.4, respectively; SAA: 10.0 ± 10.9 and 2.1 ± 0.9, respectively; LAA: 32.2 ± 15.0 and 1.8 ± 1.1, respectively]. A significant decline in monocyte CD26 expression in patients with AAAs was observed relative to the CTL group. In vitro studies demonstrated that the inhibition of DPP-4 promoted PMA-induced monocytic cells differentiation, with increased CD68 and p21 expression, regulated by extracellular signal-regulated protein kinase 1/2 activation. Furthermore, inhibition of DPP-4 significantly increased the phosphorylation of PYK2 and paxillin in PMA-induced THP-1 cell differentiation. Finally, the animal study was used to confirm the in vitro results that LAA mice showed marked macrophage infiltration in the adventitia with a decreased expression of DPP-4 as compared with SAA mice. CONCLUSIONS: Increased plasma DPP-4 activity may correlate with aneurysmal development. CD26 on monocytes plays a critical role in cell differentiation, possibly mediated by extracellular signal-regulated protein kinase 1/2-p21 axis signaling pathways and cytoskeletal proteins reassembly. Exploring the role of DPP-4 further may yield potential therapeutic insights.

1 H MR spectroscopy in cervical carcinoma using external phase array body coil at 3.0 Tesla: Prediction of poor prognostic human papillomavirus genotypes.

PURPOSE: To assess the clinical value of proton (1 H) MR spectroscopy in cervical carcinomas, in the prediction of poor prognostic human papillomavirus (HPV) genotypes as well as persistent disease following concurrent chemoradiotherapy (CCRT). MATERIALS AND METHODS: 1 H MR spectroscopy using external phase array coil was performed in 52 consecutive cervical cancer patients at 3 Tesla (T). Poor prognostic HPV genotypes (alpha-7 species or absence of HPV infection) and persistent cervical carcinoma after CCRT were recorded. Statistical significance was calculated with the Mann-Whitney two-sided nonparametric test and areas under the receiver operating characteristics curve (AUC) analysis. RESULTS: A 4.3-fold (P = 0.032) increased level of methyl resonance at 0.9 ppm was found in the poor prognostic HPV genotypes, mainly attributed to the presence of HPV18, with a sensitivity of 75%, a specificity of 81%, and an AUC of 0.76. Poor prognostic HPV genotypes were more frequently observed in patients with adeno-/adenosquamous carcinoma (Chi-square, P < 0.0001). In prediction of the four patients with persistent disease after CCRT, elevated methyl resonance demonstrated a sensitivity of 100%, a specificity of 74%, and an AUC of 0.82. CONCLUSION: 1 H MR spectroscopy at 3T can be used to depict the elevated lipid resonance levels in cervical carcinomas, as well as help to predict the poor prognostic HPV genotypes and persistent disease following CCRT. Further large studies with longer follow up times are warranted to validate our initial findings. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:899-907.

Endometrial cancer with cervical stromal invasion: diagnostic accuracy of diffusion-weighted and dynamic contrast enhanced MR imaging at 3T.

OBJECTIVES: To compare the diagnostic accuracy of diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging for detecting cervical stromal invasion in endometrial cancer. METHODS: Eighty-three consecutive women with endometrial cancer underwent preoperative evaluation in a 3-T unit, including T2-weighted, DW (b = 0 and 1000 s/mm2), and DCE MR imaging. Two radiologists independently assessed presence of cervical stromal invasion, with histopathological reference as gold standard. RESULTS: For assessing cervical stromal invasion, the diagnostic accuracy, sensitivity, and specificity, respectively for Reader 1/Reader 2, were as follows: DW MR imaging- 95.2 %/91.6 %, 91.7 %/100 %, and 95.8 %/90.1 %; DCE MR imaging- 91.6 %/88 %, 58.3 %/50 %, and 97.2 %/94.4 %. The diagnostic performance of DW MR imaging (Reader 1: areas under the receiver operating characteristic curve (AUC) = 0.98; Reader 2: AUC = 0.97) was significantly higher than that of DCE MR imaging (p = 0.009 for Reader 2) or T2-weighted MR imaging (Reader 1: p = 0.006; Reader 2: p = 0.013). Patients with cervical stromal invasion showed a significantly greater canal width (p < 0.0001) and myometrial invasion extent (p = 0.006). CONCLUSIONS: DW MR imaging has superior diagnostic performance compared with DCE MR imaging in the detection of cervical stromal invasion. KEY POINTS: • DWI demonstrates a higher accuracy than DCE in detecting cervical stromal invasion. • Tumour ADC values are similar between patients without or with cervical invasion. • Canal widening causes false-negativity on DCE and T2W but not on DWI.

Layer-by-layer assembly of quercetin-loaded zein/γPGA/low-molecular-weight chitosan/fucoidan nanosystem for targeting inflamed blood vessels.

Chitosan acts as a versatile carrier in polymeric nanoparticle (NP) for diverse drug administration routes. Delivery of antioxidants, such as quercetin (Qu) showcases potent antioxidant and anti-inflammatory properties for reduction of various cardiovascular diseases, but low water solubility limits uptake. To address this, we developed a novel layer-by-layer zein/gamma-polyglutamic acid (γPGA)/low-molecular-weight chitosan (LC)/fucoidan NP for encapsulating Qu and targeting inflamed vessel endothelial cells. We used zein (Z) and γPGA (r) to encapsulate Qu (Qu-Zr NP) exhibited notably higher encapsulation efficiency compared to zein alone. Qu-Zr NP coated with LC (Qu-ZrLC2 NP) shows a lower particle size (193.2 ± 2.9 nm), and a higher zeta potential value (35.2 ± 0.4 mV) by zeta potential and transmission electron microscopy analysis. After coating Qu-ZrLC2 NP with fucoidan, Qu-ZrLC2Fa NP presented particle size (225.16 ± 0.92 nm), zeta potential (-25.66 ± 0.51 mV) and maintained antioxidant activity. Further analysis revealed that Qu-ZrLC2Fa NP were targeted and taken up by HUVEC cells and EA.hy926 endothelial cells. Notably, we observed Qu-ZrLC2Fa NP targeting zebrafish vessels and isoproterenol-induced inflamed vessels of rat. Our layer-by-layer formulated zein/γPGA/LC/fucoidan NP show promise as a targeted delivery system for water-insoluble drugs. Qu-ZrLC2Fa NP exhibit potential as an anti-inflammatory therapeutic for blood vessels.

Endometrial cancer risk stratification using MRI radiomics: corroborating with choline metabolism.

BACKGROUND AND PURPOSE: Radiomics offers little explainability. This study aims to develop a radiomics model (Rad-Score) using diffusion-weighted imaging (DWI) to predict high-risk patients for nodal metastasis or recurrence in endometrial cancer (EC) and corroborate with choline metabolism. MATERIALS AND METHODS: From August 2015 to July 2018, 356 EC patients were enrolled. Rad-Score was developed using LASSO regression in a training cohort (n = 287) and validated in an independent test cohort (n = 69). MR spectroscopy (MRS) was also used in 230 patients. Nuclear MRS measured choline metabolites in 70 tissue samples. The performance was compared against European Society for Medical Oncology (ESMO) risk groups. A P < .05 denoted statistical significance. RESULTS: Rad-Score achieved 71.1% accuracy in the training and 71.0% in the testing cohorts. Incorporating clinical parameters of age, tumor type, size, and grade, Rad-Signature reached accuracies of 73.2% in training and 75.4% in testing cohorts, closely matching the performance to the post-operatively based ESMO's 70.7% and 78.3%. Rad-Score was significantly associated with increased total choline levels on MRS (P = .034) and tissue levels (P = .019). CONCLUSIONS: Development of a preoperative radiomics risk score, comparable to ESMO clinical standard and associated with altered choline metabolism, shows translational relevance for radiomics in high-risk EC patients. TRIAL REGISTRATION: This study was registered in ClinicalTrials.gov on 2015-08-01 with Identifier NCT02528864.

Generalizable transfer learning of automated tumor segmentation from cervical cancers toward a universal model for uterine malignancies in diffusion-weighted MRI.

PURPOSE: To investigate the generalizability of transfer learning (TL) of automated tumor segmentation from cervical cancers toward a universal model for cervical and uterine malignancies in diffusion-weighted magnetic resonance imaging (DWI). METHODS: In this retrospective multicenter study, we analyzed pelvic DWI data from 169 and 320 patients with cervical and uterine malignancies and divided them into the training (144 and 256) and testing (25 and 64) datasets, respectively. A pretrained model was established using DeepLab V3 + from the cervical cancer dataset, followed by TL experiments adjusting the training data sizes and fine-tuning layers. The model performance was evaluated using the dice similarity coefficient (DSC). RESULTS: In predicting tumor segmentation for all cervical and uterine malignancies, TL models improved the DSCs from the pretrained cervical model (DSC 0.43) when adding 5, 13, 26, and 51 uterine cases for training (DSC improved from 0.57, 0.62, 0.68, 0.70, p < 0.001). Following the crossover at adding 128 cases (DSC 0.71), the model trained by combining data from adding all the 256 patients exhibited the highest DSCs for the combined cervical and uterine datasets (DSC 0.81) and cervical only dataset (DSC 0.91). CONCLUSIONS: TL may improve the generalizability of automated tumor segmentation of DWI from a specific cancer type toward multiple types of uterine malignancies especially in limited case numbers.

Machine Learning Radiomics Signature for Differentiating Lymphoma versus Benign Splenomegaly on CT.

BACKGROUND: We aimed to develop and validate a preoperative CT-based radiomics signature for differentiating lymphoma versus benign splenomegaly. METHODS: We retrospectively analyzed CT studies from 139 patients (age range 26-93 years, 43% female) between 2011 and 2019 with histopathological diagnosis of the spleen (19 lymphoma, 120 benign) and divided them into developing (n = 79) and testing (n = 60) datasets. The volumetric radiomic features were extracted from manual segmentation of the whole spleen on venous-phase CT imaging using PyRadiomics package. LASSO regression was applied for feature selection and development of the radiomic signature, which was interrogated with the complete blood cell count and differential count. All p values < 0.05 were considered to be significant. RESULTS: Seven features were selected for constructing the radiomic signature after feature selection, including first-order statistics (10th percentile and Robust Mean Absolute Deviation), shape-based (Surface Area), and texture features (Correlation, MCC, Small Area Low Gray-level Emphasis and Low Gray-level Zone Emphasis). The radiomic signature achieved an excellent diagnostic accuracy of 97%, sensitivity of 89%, and specificity of 98%, distinguishing lymphoma versus benign splenomegaly in the testing dataset. The radiomic signature significantly correlated with the platelet and segmented neutrophil percentage. CONCLUSIONS: CT-based radiomics signature can be useful in distinguishing lymphoma versus benign splenomegaly and can reflect the changes in underlying blood profiles.

An In Vitro Evaluation of Selenium Nanoparticles on Osteoblastic Differentiation and Antimicrobial Properties against Porphyromonas gingivalis.

Despite numerous treatment methods, there is no gold standard for the treatment of peri-implantitis-an infectious peri-implant disease. Here, we examined selenium nanoparticles (SeNPs) at a wide range of concentrations to investigate their cytotoxicity, regulation of osteoblastic differentiation, and assessed the antibacterial effect against Porphyromonas gingivalis. SeNPs (mean size: 70 nm; shape: near-spherical; concentration: 0-2048 ppm) were tested against the MC3T3-E1 osteoblast precursor cell line and P. gingivalis red complex pathogen. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) analysis was used to evaluate the bone morphogenetic protein 2 (BMP-2) signaling pathway. SeNPs at concentrations of 2-16 ppm showed no obvious cytotoxicity and promoted good mineralization and calcification. SeNPs at concentrations 64 ppm and below influenced gene expression promoting osteoblastic differentiation, whereas at high concentrations inhibited the expression of Runt-related transcription factor 2 (Runx2). The growth of P. gingivalis was significantly inhibited at SeNP concentrations of more than 4 ppm. SeNPs at low concentrations promoted osteoblastic differentiation while strongly inhibiting peri-implantitis pathogen growth. This study represents one of the few in vitro assessments of SeNPs against a red complex pathogen and the regulatory effect on osteoblastic differentiation. The findings demonstrate SeNPs could potentially be used for future application on implant coating.

Tolvaptan reduces angiotensin II-induced experimental abdominal aortic aneurysm and dissection.

Tolvaptan has been approved for the treatment of autosomal dominant polycystic kidney disease and heart failure. However, the role of tolvaptan in patients with abdominal aortic aneurysm (AAA) has not been examined. Human aortic smooth muscle cells (HASMCs) were used as the in vitro model. Via Ang II infusion, experimental AAAs were induced in Apo-E knockout mice. In vitro study showed that tolvaptan suppressed matrix metalloproteinase (MMP) expressions (MMP-2 and MMP-9) and apoptosis in Ang II-stimulated HASMCs. In the Apo-E knockout mice with Ang II-induced AAA, the animals exhibited AAA formation with elastic lamina degradation, dilatation of the suprarenal aorta, increased macrophage infiltration and higher expressions of MMPs. Treatment with a high dose of tolvaptan prevented experimental AAA formation while preserving the elastic lamina structure, reducing inflammatory macrophages, and inhibiting gelatinolytic activity, MMP expressions and apoptosis of SMCs in aorta tissue. Specifically, tolvaptan reduced the expression of receptor-interacting protein kinase 3 (RIP3) and decreased apoptosis of SMCs. Our data demonstrated that tolvaptan reduces experimental AAA formation and dissection by inhibiting destruction of the aortic structure integrity and reducing inflammatory macrophage infiltration, MMP-2 and MMP-9 expressions, and apoptosis of vascular SMCs, indicating tolvaptan may have therapeutic potential for AAA and dissection.

Hydrogen Sulfide Attenuates Aortic Remodeling in Aortic Dissection Associating with Moderated Inflammation and Oxidative Stress through a NO-Dependent Pathway.

Aortic dissection (AD) is a highly lethal vascular disease characterized by separation of the constituent layers of the aortic wall. An increasing body of research indicates that inflammatory response and oxidative stress are implicated in vascular remodeling, which plays a key role in the development of AD. Hydrogen sulfide (H2S) has been found to protect against various types of cardiovascular disease, including myocardial infarction, arthrosclerosis, and hypertension. However, research on the effect of H2S on AD is insufficient. This study therefore elucidated the effect of H2S on the development and progression of AD, and the potential mechanism involved. Using ß-aminopropionitrile fumarate (BAPN) and angiotensin II (Ang-II)-induced AD animal models, the administration of NaHS (as H2S donor, 56 µmol/kg body weight/day) was found to retard the development of AD. Murine VSMCs (Movas) exposed to interleukin-6 (IL-6) (20 ng/mL) to induce phenotypic switch. Histological analyses indicated that H2S administration inhibited the accumulation of inflammatory cells in the aortic wall and the related expression of inflammatory genes. Additionally, H2S treatment elevated aortic superoxide dismutase (SOD) activity and ablated malonaldehyde (MDA) and nitric oxide (NO) levels. In mechanistic terms, H2S attenuated IL-6 induced a pathological VSMC phenotypical switch through NO modulation by N(G)-monomethyl-L-arginine acetate salt (L-NMMA) stimulation. H2S inhibits AD formation by decreasing the inflammatory response, and oxidative stress, and by positively participating in vascular remodeling. These findings suggest a role for H2S as a novel and promising therapeutic strategy to prevent AD development.

Galectin-3 as a Biomarker for Stratifying Abdominal Aortic Aneurysm Size in a Taiwanese Population.

Abdominal aortic aneurysm (AAA) ruptures are unpredictable and lethal. A biomarker predicting AAA rupture risk could help identify patients with small, screen-detected AAAs. Galectin-3 (Gal-3), a ß-galactosidase-binding lectin, is involved in inflammatory processes and may be associated with AAA incidence. We investigated whether Gal-3 can be used as a biomarker of AAA size. Plasma Gal-3 protein concentrations were examined in patients with AAA (n = 151) and control patients (n = 195) using Human ProcartaPlex multiplex and simplex kits. Circulating Gal-3 levels were significantly higher in patients with AAA than in control patients. The area under the receiver operating characteristic curve for Gal-3 was 0.91. Multivariate logistic regression analysis revealed a significant association between Gal-3 level and the presence of AAA. Circulating Gal-3 levels were significantly correlated with aortic diameter in a concentration-dependent manner. In conclusion, higher plasma Gal-3 concentrations may be a useful biomarker of AAA progression.