Salivary Lipids of Patients with Non-Small Cell Lung Cancer Show Perturbation with Respect to Plasma.

A comprehensive lipid profile was analyzed in patients with non-small cell lung cancer (NSCLC) using nanoflow ultrahigh-performance liquid chromatography-electrospray ionization-tandem mass spectrometry. This study investigated 297 and 202 lipids in saliva and plasma samples, respectively, comparing NSCLC patients to healthy controls. Lipids with significant changes (>2-fold, p < 0.05) were further analyzed in each sample type. Both saliva and plasma exhibited similar lipid alteration patterns in NSCLC, but saliva showed more pronounced changes. Total triglycerides (TGs) increased (>2-3-fold) in plasma and saliva samples. Three specific TGs (50:2, 52:5, and 54:6) were significantly increased in NSCLC for both sample types. A common ceramide species (d18:1/24:0) and phosphatidylinositol 38:4 decreased in both plasma and saliva by approximately two-fold. Phosphatidylserine 36:1 was selectively detected in saliva and showed a subsequent decrease, making it a potential biomarker for predicting lung cancer. We identified 27 salivary and 10 plasma lipids as candidate markers for NSCLC through statistical evaluations. Moreover, this study highlights the potential of saliva in understanding changes in lipid metabolism associated with NSCLC.

Comprehensive Lipid Profiling Recapitulates Enhanced Lipolysis and Fatty Acid Metabolism in Intimal Foamy Macrophages From Murine Atherosclerotic Aorta.

Lipid accumulation in macrophages is a prominent phenomenon observed in atherosclerosis. Previously, intimal foamy macrophages (FM) showed decreased inflammatory gene expression compared to intimal non-foamy macrophages (NFM). Since reprogramming of lipid metabolism in macrophages affects immunological functions, lipid profiling of intimal macrophages appears to be important for understanding the phenotypic changes of macrophages in atherosclerotic lesions. While lipidomic analysis has been performed in atherosclerotic aortic tissues and cultured macrophages, direct lipid profiling has not been performed in primary aortic macrophages from atherosclerotic aortas. We utilized nanoflow ultrahigh-performance liquid chromatography-tandem mass spectrometry to provide comprehensive lipid profiles of intimal non-foamy and foamy macrophages and adventitial macrophages from Ldlr-/- mouse aortas. We also analyzed the gene expression of each macrophage type related to lipid metabolism. FM showed increased levels of fatty acids, cholesterol esters, phosphatidylcholine, lysophosphatidylcholine, phosphatidylinositol, and sphingomyelin. However, phosphatidylethanolamine, phosphatidic acid, and ceramide levels were decreased in FM compared to those in NFM. Interestingly, FM showed decreased triacylglycerol (TG) levels. Expressions of lipolysis-related genes including Pnpla2 and Lpl were markedly increased but expressions of Lpin2 and Dgat1 related to TG synthesis were decreased in FM. Analysis of transcriptome and lipidome data revealed differences in the regulation of each lipid metabolic pathway in aortic macrophages. These comprehensive lipidomic data could clarify the phenotypes of macrophages in the atherosclerotic aorta.

Artificial intelligence-based iliofemoral deep venous thrombosis detection using a clinical approach.

Early diagnosis of deep venous thrombosis is essential for reducing complications, such as recurrent pulmonary embolism and venous thromboembolism. There are numerous studies on enhancing efficiency of computer-aided diagnosis, but clinical diagnostic approaches have never been considered. In this study, we evaluated the performance of an artificial intelligence (AI) algorithm in the detection of iliofemoral deep venous thrombosis on computed tomography angiography of the lower extremities to investigate the effectiveness of using the clinical approach during the feature extraction process of the AI algorithm. To investigate the effectiveness of the proposed method, we created synthesized images to consider practical diagnostic procedures and applied them to the convolutional neural network-based RetinaNet model. We compared and analyzed the performances based on the model's backbone and data. The performance of the model was as follows: ResNet50: sensitivity = 0.843 (± 0.037), false positives per image = 0.608 (± 0.139); ResNet152 backbone: sensitivity = 0.839 (± 0.031), false positives per image = 0.503 (± 0.079). The results demonstrated the effectiveness of the suggested method in using computed tomography angiography of the lower extremities, and improving the reporting efficiency of the critical iliofemoral deep venous thrombosis cases.

Flow Field-Flow Fractionation with a Thickness-Tapered Channel.

This study introduces the thickness-tapered channel design for flow field-flow fractionation (FlFFF) for the first time. In this design, the channel thickness linearly decreases along the channel axis such that the flow velocity increases down the channel. Channel thickness is an important variable for controlling retention time and resolution in field-flow fractionation. Especially, in the steric/hyperlayer mode of FlFFF, in which particles (>1 µm) migrate at elevated heights above the channel wall owing to hydrodynamic lift forces, the migration of long-retaining smaller-sized particles can be enhanced in a relatively thin channel or by increasing the migration flow rate; however, an upper size limit that can be resolved is simultaneously sacrificed. A thickness-tapered channel was constructed without a channel spacer by carving the surface of a channel block such that the channel inlet was deeper than the outlet (w = 400 → 200 µm). The performance of a thickness-tapered channel was evaluated using polystyrene standards and compared to that of a channel of uniform thickness (w = 300 µm) with a similar effective channel volume in terms of sample recovery, dynamic size range of separation, and steric transition under different flow rate conditions. The thickness-tapered channel can be an alternative to maintain the resolving power for particles with an upper large-diameter limit, faster separation of particles with a lower limit, and higher elution recovery without implementing the additional field-programming option.

Comparison between Deep Learning and Conventional Machine Learning in Classifying Iliofemoral Deep Venous Thrombosis upon CT Venography.

In this study, we aimed to investigate quantitative differences in performance in terms of comparing the automated classification of deep vein thrombosis (DVT) using two categories of artificial intelligence algorithms: deep learning based on convolutional neural networks (CNNs) and conventional machine learning. We retrospectively enrolled 659 participants (DVT patients, 282; normal controls, 377) who were evaluated using contrast-enhanced lower extremity computed tomography (CT) venography. Conventional machine learning consists of logistic regression (LR), support vector machines (SVM), random forests (RF), and extreme gradient boosts (XGB). Deep learning based on CNN included the VGG16, VGG19, Resnet50, and Resnet152 models. According to the mean generated AUC values, we found that the CNN-based VGG16 model showed a 0.007 higher performance (0.982 ± 0.014) as compared with the XGB model (0.975 ± 0.010), which showed the highest performance among the conventional machine learning models. In the conventional machine learning-based classifications, we found that the radiomic features presenting a statistically significant effect were median values and skewness. We found that the VGG16 model within the deep learning algorithm distinguished deep vein thrombosis on CT images most accurately, with slightly higher AUC values as compared with the other AI algorithms used in this study. Our results guide research directions and medical practice.

In Vivo Animal Study of a Highly Viscous N-butyl Cyanoacrylate Medical Adhesive for Intravenous Embolization.

N-butyl cyanoacrylate (NBCA) is a liquid monomer that undergoes an exothermic polymerization reaction to form a solid upon initiation with hydroxyl anions. Recently, EGpresto, a highly viscous NBCA-based adhesive, has been developed for vascular-occlusion purposes. In this study, we investigated the heat of polymerization of EGpresto and compared the results with those of a low-viscosity NBCA glue. Results show that EGpresto exhibited a lower heat of polymerization (64 ± 7 °C vs. 34 ± 1 °C). This was due to its high viscosity, which resulted in a delayed polymerization time. To investigate the efficacy and safety of EGpresto for intravenous embolization, a 14 d in vivo animal test was conducted using three pigs. Five cc of EGpresto was injected into the epigastric vein of each animal. Complete postoperative vein occlusion was confirmed at 7 and 14 d by ultrasonographic visualization. After the animals were sacrificed, the operated and unoperated veins were exposed, and the injected adhesive was found without migration. During the histology, the injected adhesive was not found in the inner or outer vein walls, and the immune reactions seemed to be the only foreign-body reaction, showing that EGpresto is a non-toxic and safe intravascular embolic agent.

A deep learning algorithm for automated measurement of vertebral body compression from X-ray images.

The vertebral compression is a significant factor for determining the prognosis of osteoporotic vertebral compression fractures and is generally measured manually by specialists. The consequent misdiagnosis or delayed diagnosis can be fatal for patients. In this study, we trained and evaluated the performance of a vertebral body segmentation model and a vertebral compression measurement model based on convolutional neural networks. For vertebral body segmentation, we used a recurrent residual U-Net model, with an average sensitivity of 0.934 (± 0.086), an average specificity of 0.997 (± 0.002), an average accuracy of 0.987 (± 0.005), and an average dice similarity coefficient of 0.923 (± 0.073). We then generated 1134 data points on the images of three vertebral bodies by labeling each segment of the segmented vertebral body. These were used in the vertebral compression measurement model based on linear regression and multi-scale residual dilated blocks. The model yielded an average mean absolute error of 2.637 (± 1.872) (%), an average mean square error of 13.985 (± 24.107) (%), and an average root mean square error of 3.739 (± 2.187) (%) in fractured vertebral body data. The proposed algorithm has significant potential for aiding the diagnosis of vertebral compression fractures.

Small intestine- and colon-specific smart oral drug delivery system with controlled release characteristic.

In recent years, there has been a significant increase in strategies for the development of small intestine (and colon)-specific oral drug-delivery systems to maximize the efficiency of therapeutic agents and reduce side effects. However, only a few strategies are capable of working in the complicated environment of the human intestinal tract. In this study, the preparation of a basic pH/temperature-responsive co-polymer (p-NIVIm) and its in-vitro-drug delivery function in the pH range of 1-8 and temperature range of 25-42 °C are reported. The basic copolymer was prepared by radical copolymerization of N-isopropyl acryl amide (NIPAAm) and N-vinylimidazole (VIm). The lower critical solution temperature (LCST) of p-NIVIm was higher in stomach pH (~1.0) conditions (36.5-42 °C) and lower in small intestine and/or colon pH (~8.0) conditions (35.8-38.2 °C). The ability to uptake a model protein (BSA) at body temperature and to release it in conditions of 37 °C and pH 1-8 was determined. The drug loading capacity (0.231 mg per 1.0 mg copolymer) and efficiency (92.4%) were high at 37 °C/pH 7. The drug carrier showed a slow release pattern at pH 1 (~0.084 mg; ~35%) and then a sudden release pattern (~0.177 mg; ~73%) at pH 8. The cytotoxicity of p-NIVIm to MCF-7 cells in vitro was minimal at concentrations <168.9 µg/mL after 72 h. The prepared copolymer with its pH-/temperature-responsive protein-entrapping and -releasing behavior at body temperature may potentially be applied as a novel small intestine (and colon)-specific oral drug delivery system.

Simple and cost-effective method of highly conductive and elastic carbon nanotube/polydimethylsiloxane composite for wearable electronics.

The development of various flexible and stretchable materials has attracted interest for promising applications in biomedical engineering and electronics industries. This interest in wearable electronics, stretchable circuits, and flexible displays has created a demand for stable, easily manufactured, and cheap materials. However, the construction of flexible and elastic electronics, on which commercial electronic components can be mounted through simple and cost-effective processing, remains challenging. We have developed a nanocomposite of carbon nanotubes (CNTs) and polydimethylsiloxane (PDMS) elastomer. To achieve uniform distributions of CNTs within the polymer, an optimized dispersion process was developed using isopropyl alcohol (IPA) and methyl-terminated PDMS in combination with ultrasonication. After vaporizing the IPA, various shapes and sizes can be easily created with the nanocomposite, depending on the mold. The material provides high flexibility, elasticity, and electrical conductivity without requiring a sandwich structure. It is also biocompatible and mechanically stable, as demonstrated by cytotoxicity assays and cyclic strain tests (over 10,000 times). We demonstrate the potential for the healthcare field through strain sensor, flexible electric circuits, and biopotential measurements such as EEG, ECG, and EMG. This simple and cost-effective fabrication method for CNT/PDMS composites provides a promising process and material for various applications of wearable electronics.

In vivo evaluation of hot water extract of Acorus gramineus root against benign prostatic hyperplasia.

BACKGROUND: Acorus gramineus has been reported to exhibit various pharmacological effects including inhibition of cholesterol synthesis, enhancement of lipid metabolism, prevention of dementia and inhibition of mast cell growth. According to the Chinese compendium of materia media, it has been reported that Acorus spp. is effective for sedation, dementia prevention as well as diuretic effect. In addition, it showed more than equivalent activity compared to furosoemide, a drug known to be effective in diuretic action in animal model study. However, their effectiveness against benign prostatic hyperplasia (BPH) of Acorus gramineus has not been reported. This study was designed to evaluate the effect of Acorus gramineus root hot water extract (AG) against BPH in vivo. METHODS: Male rats, 10 weeks of age and weighing 405 g ± 10 g, were used for this study. Biomarkers were evaluated including prostate weight, prostate weight ratio, hormonal changes, 5-α reductase type II androgen receptor (AR) of the prostate gland and anti-oxidant activation factors related to BPH. These biomarkers were measured in vivo test. RESULTS: AG showed significant effect at the 250 and 500 mg/kg/day in rats. Groups treated with AG displayed significantly lower levels of prostate gland weight (0.79 g) compared to the BPH induced group (1.19 g). Also, dihydrotestosterone (DHT) level was decreased from 61.8 to 100% and androgen receptor expression level was decreased from 111 to 658%. Any hematological toxicity of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) level wasn't observed. CONCLUSION: This study indicated that AG was effective for reducing BPH symptoms. TRIAL REGISTRATION: Not applicable.

Ionic and thermo-switchable polymer-masked mesoporous silica drug-nanocarrier: High drug loading capacity at 10°C and fast drug release completion at 40°C.

The preparation of the ideal smart drug-delivery systems were successfully achieved by the in situ co-polymerization of a vinyl group-functionalized mesoporous silica nanoparticle (f-MSN) with 1-butyl-3-vinyl imidazolium bromide (BVIm) and N-isopropylacrylamide (NIPAAm) monomers. The thickness of the capping copolymer layer, poly(NIPAAm-co-BVIm) (p-NIBIm), was controlled at between 2.5nm and 5nm, depending on the monomers/f-MSN ratio in the reaction solution. The finally obtained smart drug-delivery systems are named as p-MSN2.5 and p-MSN5.0 (MSNs integrated by 2.5nm and 5nm p-NIBIm layer in thickness). The key roles of the mesoporous-silica-nanoparticle (MSN) core and the p-NIBIm shell are drug-carrying (or containing) and pore-capping, respectively, and the latter has an on/off function that operates in accordance with temperature changes. According to the swelling- or shrinking-responses of the smart capping copolymer to temperature changes between 10°C and 40°C, the loading and releasing patterns of the model drug cytochrome c were studied in vitro. The developed system showed interesting performances such as a cytochrome-c-loading profile (loading capacity for 3h=26.3% and 19.8% for p-MSN2.5 and p-MSN5.0, respectively) at 10°C and a cytochrome-c-releasing profile (releasing efficiency=>95% within 3 days and 4 days for p-MSN2.5 and p-MSN5.0, respectively) at 40°C. The cytotoxicity of the drug delivery systems, p-MSN2.5 and p-MSN5.0 (in the concentration range of <0.125mg/mL without drug), for human embryonic kidney (HEK 293) cells were minimal in vitro compared with that of a blank MSN. These results may be reasonably applied in the field of specified drug delivery.

Triple Hit with Drug Carriers: pH- and Temperature-Responsive Theranostics for Multimodal Chemo- and Photothermal Therapy and Diagnostic Applications.

Currently there is a strong need for new drug delivery systems, which enable targeted and controlled function in delivering drugs while satisfying highly sensitive imaging modality for early detection of the disease symptoms and damaged sites. To meet these criteria we develop a system that integrates therapeutic and diagnostic capabilities (theranostics). Importantly, therapeutic efficacy of the system is enhanced by exploiting synergies between nanoparticles, drug, and hyperthermia. At the core of our innovation is near-infrared (NIR) responsive gold nanorods (Au) coated with drug reservoirs--mesoporous silica shell (mSi)--that is capped with thermoresponsive polymer. Such design of theranostics allows the detection of the system using computed tomography (CT), while finely controlled release of the drug is achieved by external trigger, NIR light irradiation--ON/OFF switch. Doxorubicin (DOX) was loaded into mSi formed on the gold core (Au@mSi-DOX). Pores were then capped with the temperature-sensitive poly(N-isopropylacrylamide)-based N-butyl imidazolium copolymer (poly(NIPAAm-co-BVIm)) resulting in a hybrid system-Au@mSi-DOX@P. A 5 min exposure to NIR induces polymer transition, which triggers the drug release (pores opening), increases local temperature above 43 °C (hyperthermia), and upregulates particle uptake (polymer becomes hydrophilic). The DOX release is also triggered by drop in pH enabling localized drug release when particles are taken up by cancer cells. Importantly, the synergies between chemo- and photothermal therapy for DOX-loaded theranostics were confirmed. Furthermore, higher X-ray attenuation value of the theranostics was confirmed via X-ray CT test indicating that the nanoparticles act as contrast agent and can be detected by CT.

Production of CNT-taxol-embedded PCL microspheres using an ammonium-based room temperature ionic liquid: as a sustained drug delivery system.

We describe a one-pot method for the mass production of polymeric microspheres containing water-soluble carbon-nanotube (w-CNT)-taxol complexes using an ammonium-based room temperature ionic liquid. Polycaprolactone (PCL), trioctylmethylammonium chloride (TOMAC; liquid state from -20 to 240°C), and taxol were used, respectively, as a model polymer, room temperature ionic liquid, and drug. Large quantities of white colored PCL powder without w-CNT-taxol complexes and gray colored PCL powders containing w-CNT-taxol (1:1 or 1:2 wt/wt) complexes were produced by phase separation between the hydrophilic TOMAC and the hydrophobic PCL. Both microsphere types had a uniform, spherical structure of average diameter 3-5µm. The amount of taxol embedded in PCL microspheres was determined by HPLC and (1)H NMR to be 8-12µg per 1.0mg of PCL (loading capacity (LC): 0.8-1.2%; entrapment efficiency (EE): 16-24%). An in vitro HPLC release assay showed sustain release of taxol without an initial burst over 60days at an average rate of 0.003-0.0073mg per day. The viability patterns of human breast cancer cells (MCF-7) for PCTx-1 and -2 showed dose-dependent inhibitory effects. In the presence of PCTx-1 and -2, the MCF-7 cells showed high viability in the concentration level of, respectably, <70 and <5µg/mL.

Left ventricular metastasis from renal cell carcinoma causing left ventricular outflow tract obstruction.

Most cases of cardiac metastasis from renal cell carcinoma (RCC) involve the vena cava or right atrium. Left ventricular metastases from RCC without involving the vena cava or right atrium are extremely rare. Herein we report a case of RCC with left ventricular metastasis causing left ventricular outflow obstruction (LVOT).

A phase II study of combination chemotherapy with docetaxel and carboplatin for elderly patients with advanced non-small cell lung cancer.

BACKGROUND: More than 50% of all advanced non-small cell lung cancer (NSCLC) is diagnosed in patients older than 65 years. Chemotherapy in elderly patients has not been standardized even though cisplatin-based chemotherapy has been used in patients with advanced NSCLC as primary therapy. We investigated the efficacy and safety of combination chemotherapy with docetaxel and carboplatin for elderly patients with advanced NSCLC. METHODS: Chemotherapy-naïve patients (age > or = 65 years) with stage IIIB or IV NSCLC were enrolled. Patients received docetaxel (75 mg/m(2) on D1) and carboplatin (AUC of 5mg/ml/min on D1) every 3 weeks. The end points included the response rate, progression-free survival (PFS), overall survival (OS) and toxicity. RESULTS: A total of 43 patients was enrolled between March 2005 and December 2008, and 38 patients were evaluable. The median age was 74 years old (range, 65-84 years) and 39 patients (90.6%) had an ECOG PS of 0 or 1. Squamous cell carcinoma was observed in 18 patients (41.8%) and 24 patients (55.8%) had an increased Charlson comorbidity index score (CCI > or = 1). The median number of treatment cycles was five (range, 1-8) and the relative dose intensity was 90.4% for docetaxel and 92.7% for carboplatin. The overall response rate was 46.5% (95% CI, 31.6-61.4) for with one complete response and 19 partial responses. The median follow-up duration was 14.4 months. The median PFS was 6.9 months (95% CI, 6.25-7.55) and the median OS was 13.1 months (95% CI, 10.20-16.07). The 1-year survival rate was 60%. In grade 3 or 4 hematological toxicities, neutropenia (37.2%), anemia (18.6%) and thrombocytopenia (4.6%) were shown. The non-hematological toxicities were tolerable. CONCLUSIONS: The combination chemotherapy with docetaxel and carboplatin was effective with tolerable toxicities in elderly patients with advanced non-small cell lung cancer.