Classifying breast cancer using multi-view graph neural network based on multi-omics data.

Introduction: As the evaluation indices, cancer grading and subtyping have diverse clinical, pathological, and molecular characteristics with prognostic and therapeutic implications. Although researchers have begun to study cancer differentiation and subtype prediction, most of relevant methods are based on traditional machine learning and rely on single omics data. It is necessary to explore a deep learning algorithm that integrates multi-omics data to achieve classification prediction of cancer differentiation and subtypes. Methods: This paper proposes a multi-omics data fusion algorithm based on a multi-view graph neural network (MVGNN) for predicting cancer differentiation and subtype classification. The model framework consists of a graph convolutional network (GCN) module for learning features from different omics data and an attention module for integrating multi-omics data. Three different types of omics data are used. For each type of omics data, feature selection is performed using methods such as the chi-square test and minimum redundancy maximum relevance (mRMR). Weighted patient similarity networks are constructed based on the selected omics features, and GCN is trained using omics features and corresponding similarity networks. Finally, an attention module integrates different types of omics features and performs the final cancer classification prediction. Results: To validate the cancer classification predictive performance of the MVGNN model, we conducted experimental comparisons with traditional machine learning models and currently popular methods based on integrating multi-omics data using 5-fold cross-validation. Additionally, we performed comparative experiments on cancer differentiation and its subtypes based on single omics data, two omics data, and three omics data. Discussion: This paper proposed the MVGNN model and it performed well in cancer classification prediction based on multiple omics data.

Cyanidin-3-O-Glucoside Alleviates Alcoholic Liver Injury via Modulating Gut Microbiota and Metabolites in Mice.

Alcoholic liver disease (ALD) is primarily caused by long-term excessive alcohol consumption. Cyanidin-3-O-glucoside (C3G) is a widely occurring natural anthocyanin with multiple biological activities. This study aims to investigate the effects of C3G isolated from black rice on ALD and explore the potential mechanism. C57BL/6J mice (male) were fed with standard diet (CON) and Lieber-DeCarli liquid-fed (Eth) or supplemented with a 100 mg/kg/d C3G Diet (Eth-C3G), respectively. Our results showed that C3G could effectively ameliorate the pathological structure and liver function, and also inhibited the accumulation of liver lipids. C3G supplementation could partially alleviate the injury of intestinal barrier in the alcohol-induced mice. C3G supplementation could increase the abundance of Norank_f_Muribaculaceae, meanwhile, the abundances of Bacteroides, Blautia, Collinsella, Escherichia-Shigella, Enterococcus, Prevotella, [Ruminococcus]_gnavus_group, Methylobacterium-Methylorubrum, Romboutsia, Streptococcus, Bilophila, were decreased. Spearman's correlation analysis showed that 12 distinct genera were correlated with blood lipid levels. Non-targeted metabolic analyses of cecal contents showed that C3G supplementation could affect the composition of intestinal metabolites, particularly bile acids. In conclusion, C3G can attenuate alcohol-induced liver injury by modulating the gut microbiota and metabolites, suggesting its potential as a functional food ingredient against alcoholic liver disease.

Redox-sensitive self-assembling polymer micelles based on oleanolic modified hydroxyethyl starch: Synthesis, characterisation, and oleanolic release.

Our study aimed at developing polymer micelles that possess redox sensitivity and excellent controlled release properties. 3,3'-dithiodipropionic acid (DTDPA, Abbreviation in synthetic polymers: SS) was introduced as ROS (Reactive oxygen species)response bond and connecting arm to couple hydroxyethyl starch (HES) with oleanolic acid (OA), resulting in the synthesis of four distinct grafting ratios of HES-SS-OA. FTIR (Fourier Transform infrared spectroscopy) and 1H NMR (1H Nuclear magnetic resonance spectra) were used to verify the triumphant combination of HES-SS-OA. Polymer micelles were found to encapsulate OA in an amorphous form, as indicated by the results of XRD (X-ray diffraction) and DSC (Differential scanning calorimetry). When the OA grafting rate on HES increased from 7.72 % to 11.75 %, the particle size decreased from 297.79 nm to 201.39 nm as the polymer micelles became compact due to enhanced hydrophobicity. In addition, the zeta potential changed from -16.42 mv to -25.78 mv, the PDI (polydispersity index) decreased from 0.3649 to 0.2435, and the critical micelle concentration (CMC) decreased from 0.0955 mg/mL to 0.0123 mg/mL. Results of erythrocyte hemolysis, cytotoxicity and cellular uptake illustrated that HES-SS-OA had excellent biocompatibility and minimal cytotoxicity for AML-12 cells. Disulfide bond breakage of HES-SS-OA in the presence of H2O2 and GSH confirmed the redox sensitivity of the HES-SS-OA micelles and their excellent controlled release properties for OA. These findings suggest that HES-SS-OA can be potentially used in the future as a healthcare drug and medicine for the prevention or adjuvant treatment of inflammation.

Consistency label-activated region generating network for weakly supervised medical image segmentation.

The current methods of auto-segmenting medical images are limited due to insufficient and ambiguous pathonmorphological labeling. In clinical practice, rough classification labels (such as disease or normal) are more commonly used than precise segmentation masks. However, there is still much to be explored regarding utilizing these weak clinical labels to accurately determine the lesion mask and guide medical image segmentation. In this paper, we proposed a weakly supervised medical image segmentation model to directly generate the lesion mask through a class activation map (CAM) guided cycle-consistency label-activated region transferring network. Cycle-consistency enforces that the mappings between the two domains should be reversible, which ensures that the original image can be reconstructed from the translated image. We developed a complementary branches fusion module to address the issue of blurry boundaries in CAM-guided segmentation. The complementary branch preserves the original semantic information of the non-lesion region and perfectly fuses the transferred feature of the lesion region with a complementary mask-constrained fake image generation process to clear the boundary of the lesion and non-lesion regions. This module allows the class transformation to focus solely on the label-activated region, resulting in more explicit segmentation. This model can accurately identify different region of medical images at the pixel-level while preserving the overall semantic structure semantion. It organizes disease labels and corresponding regions during image synthesis. Our method utilizes a joint discrimination strategy that significantly enhances the precision of the produced lesion mask. Extensive experiments of the proposed method on BraTs, ISIC and COVID-19 datasets demonstrate superior performance over existing state-of-the-art methods. The code and datasets are available at: https://github.com/mlcb-jlu/MedImgSeg.

Kled: an ultra-fast and sensitive structural variant detection tool for long-read sequencing data.

Structural Variants (SVs) are a crucial type of genetic variant that can significantly impact phenotypes. Therefore, the identification of SVs is an essential part of modern genomic analysis. In this article, we present kled, an ultra-fast and sensitive SV caller for long-read sequencing data given the specially designed approach with a novel signature-merging algorithm, custom refinement strategies and a high-performance program structure. The evaluation results demonstrate that kled can achieve optimal SV calling compared to several state-of-the-art methods on simulated and real long-read data for different platforms and sequencing depths. Furthermore, kled excels at rapid SV calling and can efficiently utilize multiple Central Processing Unit (CPU) cores while maintaining low memory usage. The source code for kled can be obtained from https://github.com/CoREse/kled.

Untargeted Metabolomic Analyses and Antilipidemic Effects of Citrus Physiological Premature Fruit Drop.

Increasingly globally prevalent obesity and related metabolic disorders have underscored the demand for safe and natural therapeutic approaches, given the limitations of weight loss drugs and surgeries. This study compared the phytochemical composition and antioxidant activity of five different varieties of citrus physiological premature fruit drop (CPFD). Untargeted metabolomics was employed to identify variations in metabolites among different CPFDs, and their antilipidemic effects in vitro were assessed. The results showed that Citrus aurantium L. 'Daidai' physiological premature fruit drop (DDPD) and Citrus aurantium 'Changshan-huyou' physiological premature fruit drop (HYPD) exhibited higher levels of phytochemicals and stronger antioxidant activity. There were 97 differential metabolites identified in DDPD and HYPD, including phenylpropanoids, flavonoids, alkaloids, organic acids, terpenes, and lipids. Additionally, DDPD and HYPD demonstrated potential antilipidemic effects against oleic acid (OA)-induced steatosis in HepG2 hepatocytes and 3T3-L1 adipocytes. In conclusion, our findings reveal the outstanding antioxidant activity and antilipidemic effects of CPFD, indicating its potential use as a natural antioxidant and health supplement and promoting the high-value utilization of this resource.

Lemon essential oil nanoemulsions: Potential natural inhibitors against Escherichia coli.

Lemon essential oil (LEO) is a common natural antibacterial substance, and encapsulating LEO into nanoemulsions (NEs) can improve their stability and broaden its application. Our study aimed to investigate the bacterial inhibitory effect of LEO-NEs against Escherichia coli (E. coli). Results showed that the minimum inhibitory concentration (MIC) of LEO-NEs was 6.25 mg/mL, and the time-kill curve showed that E. coli were significantly killed by LEO-NEs after 5 h of treatment at 1MIC. Flow-cytometry analysis showed that LEO-NEs adversely affected the cell-membrane depolarisation, cell-membrane integrity, and efflux pump function of E. coli. Confocal laser scanning microscopy demonstrated that 8MIC of LEO-NEs induced changes in the cell-membrane permeability and cell-wall integrity of E. coli. Proteomic results suggested that the mode of action LEO-NEs against E. coli was to enhance bacterial chemotaxis and significantly inhibit ribosomal assembly. They may also affect butyric acid, ascorbic acid and aldehyde metabolism, and sulphur-relay system pathways. In conclusion, LEO-NEs had potential application as a natural antibacterial agent for the control of E. coli in the food industry.

Machine learning aided non-invasive diagnosis of coronary heart disease based on tongue features fusion.

BACKGROUND: Coronary heart disease (CHD) is the first cause of death globally. Hypertension is considered to be the most important independent risk factor for CHD. Early and accurate diagnosis of CHD in patients with hypertension can plays a significant role in reducing the risk and harm of hypertension combined with CHD. OBJECTIVE: To propose a non-invasive method for early diagnosis of coronary heart disease according to tongue image features with the help of machine learning techniques. METHODS: We collected standard tongue images and extract features by Diagnosis Analysis System (TDAS) and ResNet-50. On the basis of these tongue features, a common machine learning method is used to customize the non-invasive CHD diagnosis algorithm based on tongue image. RESULTS: Based on feature fusion, our algorithm has good performance. The results showed that the XGBoost model with fused features had the best performance with accuracy of 0.869, the AUC of 0.957, the AUPR of 0.961, the precision of 0.926, the recall of 0.806, and the F1-score of 0.862. CONCLUSION: We provide a feasible, convenient, and non-invasive method for the diagnosis and large-scale screening of CHD. Tongue image information is a possible effective marker for the diagnosis of CHD.

Personalized tumor combination therapy optimization using the single-cell transcriptome.

BACKGROUND: The precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the cancer treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect the heterogeneity of malignant tumors in vivo and the immune microenvironment, motivating the need to use single-cell transcriptomes for personalized cancer treatment. METHODS: Here, we present comboSC, a computational proof-of-concept study to explore the feasibility of personalized cancer combination therapy optimization using single-cell transcriptomes. ComboSC provides a workable solution to stratify individual patient samples based on quantitative evaluation of their personalized immune microenvironment with single-cell RNA sequencing and maximize the translational potential of in vitro cellular response to unify the identification of synergistic drug/small molecule combinations or small molecules that can be paired with immune checkpoint inhibitors to boost immunotherapy from a large collection of small molecules and drugs, and finally prioritize them for personalized clinical use based on bipartition graph optimization. RESULTS: We apply comboSC to publicly available 119 single-cell transcriptome data from a comprehensive set of 119 tumor samples from 15 cancer types and validate the predicted drug combination with literature evidence, mining clinical trial data, perturbation of patient-derived cell line data, and finally in-vivo samples. CONCLUSIONS: Overall, comboSC provides a feasible and one-stop computational prototype and a proof-of-concept study to predict potential drug combinations for further experimental validation and clinical usage using the single-cell transcriptome, which will facilitate and accelerate personalized tumor treatment by reducing screening time from a large drug combination space and saving valuable treatment time for individual patients. A user-friendly web server of comboSC for both clinical and research users is available at www.combosc.top . The source code is also available on GitHub at https://github.com/bm2-lab/comboSC .

Reveal the relationship between the quality and the cuticle composition of Satsuma mandarin (Citrus unshiu) by postharvest heat treatment.

To investigate the influence of heat treatment (HT) on Satsuma mandarin fruit's postharvest quality and cuticle composition, we immersed the fruit for 3 min in hot water at 52°C and subsequently stored them at room temperature (25°C) for 28 days, and fruit quality parameters, such as good fruit rate, weight loss rate, firmness, total soluble solids, total titratable acidity, and ascorbic acid content, were monitored. Additionally, changes in the peel's cuticle composition were analyzed, and wax crystal morphologies on the fruit surface were examined using scanning electron microscopy (SEM). The findings revealed that appropriate HT effectively preserved fruit quality. The main compositions of wax and cutin on the fruit's surface remained consistent between the HT and the CK during storage. The total content of wax and cutin initially increased, peaking on the 14th day of storage, and then decreased, falling below the levels observed on day 0. Notably, the total amount of cutin in the HT group exceeded that of the control group. Specifically, ω-hydroxy fatty acids with mid-chain oxo groups and mid-oh-ω-hydroxy fatty acids constituted approximately 90% of the total cutin content. Moreover, the HT group exhibited higher (p < 0.05) total wax content in relation to the control. Fatty acids and alkanes were the predominant components, accounting for approximately 87.5% of the total wax. SEM analysis demonstrated that HT caused wax crystals to melt and redistribute, effectively filling wax gaps. It suggests that HT holds promising potential as a green, safe, and eco-friendly commercial treatment for preserving the postharvest quality of Satsuma mandarin. PRACTICAL APPLICATION: In this study, Satsuma citrus (Citrus unshiu) underwent heat treatment (HT) and was subsequently preserved at room temperature (25°C) for 28 days. The findings revealed that HT significantly improved fruit quality compared to the control group. These findings provide valuable insights into the advancement of eco-friendly and pollution-free citrus preservation methods, offering essential strategies and process parameters for their practical application.

cGAS-STING Pathway Activation and Systemic Anti-Tumor Immunity Induction via Photodynamic Nanoparticles with Potent Toxic Platinum DNA Intercalator Against Uveal Melanoma.

The cGAS-STING pathway, as a vital innate immune signaling pathway, has attracted considerable attention in tumor immunotherapy research. However, STING agonists are generally incapable of targeting tumors, thus limiting their clinical applications. Here, a photodynamic polymer (P1) is designed to electrostatically couple with 56MESS-a cationic platinum (II) agent-to form NPPDT -56MESS. The accumulation of NPPDT -56MESS in the tumors increases the efficacy and decreases the systemic toxicity of the drugs. Moreover, NPPDT -56MESS generates reactive oxygen species (ROS) under the excitation with an 808 nm laser, which then results in the disintegration of NPPDT -56MESS. Indeed, the ROS and 56MESS act synergistically to damage DNA and mitochondria, leading to a surge of cytoplasmic double-stranded DNA (dsDNA). This way, the cGAS-STING pathway is activated to induce anti-tumor immune responses and ultimately enhance anti-cancer activity. Additionally, the administration of NPPDT -56MESS to mice induces an immune memory effect, thus improving the survival rate of mice. Collectively, these findings indicate that NPPDT -56MESS functions as a chemotherapeutic agent and cGAS-STING pathway agonist, representing a combination chemotherapy and immunotherapy strategy that provides novel modalities for the treatment of uveal melanoma.

Chewing Gum Cannot Reduce Postoperative Abdominal Pain and Nausea After Posterior Spinal Fusions in Patients With Adolescent Idiopathic Scoliosis: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

STUDY DESIGN: A systematic review and meta-analysis of randomized controlled trials. OBJECTIVE: The aim of this study was to determine the effect of chewing gum on postoperative abdominal pain, nausea, and hospital stays after posterior spinal fusions (PSFs) in patients with adolescent idiopathic scoliosis (AIS). SUMMARY OF BACKGROUND DATA: Chewing gum had been extensively reported to improve bowel motility and is recommended to hasten bowel recovery following gastrointestinal surgery. However, there is no conclusive evidence regarding the effect of chewing gum on postoperative abdominal pain, nausea, and hospital stays after PSFs in AIS patients. METHODS: A comprehensive literature search was performed for relevant randomized controlled trials using PubMed, Cochrane Central Register of Controlled Trials, Web of Science, and Embase. Studies were selected to compare the use of chewing gum versus standard care in the management of postoperative abdominal pain and nausea in AIS patients undergoing PSFs. Hospital stays were also investigated. The study was conducted using the checklist for PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). RESULTS: Three randomized controlled trials were included in the systematic review and the meta-analysis. No significant effect of chewing gum was highlighted concerning the postoperative abdominal pain scores at 24 and 48 hours [24 h: mean difference (MD)=0.45, 95% CI=-0.97 to 0.07, P =0.09; 48 h: MD=-0.24, 95% CI=-0.79 to 0.32, P =0.41]. No significant difference regarding the postoperative nausea scores was found at 24 and 48 hours (24 h: MD=0.26, 95% CI=-0.27 to 0.79, P =0.34; 48 h: MD=0.06, 95% CI=-0.36 to 0.48, P =0.77). No significant difference regarding hospital stays was found (MD=0.13, 95% CI=-0.02 to 0.28, P =0.09). CONCLUSIONS: Based on the current studies, chewing gum does not have a significant effect on postoperative abdominal pain, nausea, or hospital stays after PSFs in AIS patients. As the effect of chewing gum in reducing postoperative abdominal pain exhibits a tendency towards statistical significance ( P =0.09), the effect of chewing gum in spinal surgery merits further studies with larger sample size.

Local flux coordination and global gene expression regulation in metabolic modeling.

Genome-scale metabolic networks (GSMs) are fundamental systems biology representations of a cell's entire set of stoichiometrically balanced reactions. However, such static GSMs do not incorporate the functional organization of metabolic genes and their dynamic regulation (e.g., operons and regulons). Specifically, there are numerous topologically coupled local reactions through which fluxes are coordinated; the global growth state often dynamically regulates many gene expression of metabolic reactions via global transcription factor regulators. Here, we develop a GSM reconstruction method, Decrem, by integrating locally coupled reactions and global transcriptional regulation of metabolism by cell state. Decrem produces predictions of flux and growth rates, which are highly correlated with those experimentally measured in both wild-type and mutants of three model microorganisms Escherichia coli, Saccharomyces cerevisiae, and Bacillus subtilis under various conditions. More importantly, Decrem can also explain the observed growth rates by capturing the experimentally measured flux changes between wild-types and mutants. Overall, by identifying and incorporating locally organized and regulated functional modules into GSMs, Decrem achieves accurate predictions of phenotypes and has broad applications in bioengineering, synthetic biology, and microbial pathology.

Targeting Bcl-xL is a potential therapeutic strategy for extranodal NK/T cell lymphoma.

Extranodal natural killer/T cell lymphoma, nasal type (ENKTL) is an aggressive lymphoid malignancy with a poor prognosis and lacks standard treatment. Targeted therapies are urgently needed. Here we systematically investigated the druggable mechanisms through chemogenomic screening and identified that Bcl-xL-specific BH3 mimetics effectively induced ENKTL cell apoptosis. Notably, the specific accumulation of Bcl-xL, but not other Bcl-2 family members, was verified in ENKTL cell lines and patient tissues. Furthermore, Bcl-xL high expression was shown to be closely associated with worse patient survival. The critical role of Bcl-xL in ENKTL cell survival was demonstrated utilizing selective inhibitors, genetic silencing, and a specific degrader. Additionally, the IL2-JAK1/3-STAT5 signaling was implicated in Bcl-xL dysregulation. In vivo, Bcl-xL inhibition reduced tumor burden, increased apoptosis, and prolonged survival in ENKTL cell line xenograft and patient-derived xenograft models. Our study indicates Bcl-xL as a promising therapeutic target for ENKTL, warranting monitoring in ongoing clinical trials by targeting Bcl-xL.

Retention of buoyant plastic in a well-mixed estuary due to tides, river discharge and winds.

Estuaries can act as plastic retention hotspots, but the hydrodynamic controls on retention are not well understood. This study investigates the retention of river-sourced buoyant plastics in a well-mixed estuary, the Waitemata Estuary, using validated numerical simulations of floats with different tides, winds, and freshwater discharge. The proportion of floats grounded on the shore in all seven simulations is higher than 60 % and over 90 % in five simulations after ten days. <20 % of the floats leave the estuarine mouth in any of the simulations. An increase of two orders of magnitude in freshwater discharge doubles the likelihood for floats to reach the lower estuary. However, we find increased freshwater discharge doubles the lateral circulation towards the shore and results in similar proportions of grounding (90 %) as the low discharge cases. These findings challenge the conventional view that plastics preferentially enter the open ocean after high river discharge.

Physics-informed neural networks (PINNs) for 4D hemodynamics prediction: An investigation of optimal framework based on vascular morphology.

Hemodynamic parameters are of great significance in the clinical diagnosis and treatment of cardiovascular diseases. However, noninvasive, real-time and accurate acquisition of hemodynamics remains a challenge for current invasive detection and simulation algorithms. Here, we integrate computational fluid dynamics with our customized analysis framework based on a multi-attribute point cloud dataset and physics-informed neural networks (PINNs)-aided deep learning modules. This combination is implemented by our workflow that generates flow field datasets within two types of patient personalized models - aorta with fine coronary branches and abdominal aorta. Deep learning modules with or without an antecedent hierarchical structure model the flow field development and complete the mapping from spatial and temporal dimensions to 4D hemodynamics. 88,000 cases on 4 randomized partitions in 16 controlled trials reveal the hemodynamic landscape of spatio-temporal anisotropy within two types of personalized models, which demonstrates the effectiveness of PINN in predicting the space-time behavior of flow fields and gives the optimal deep learning framework for different blood vessels in terms of balancing the training cost and accuracy dimensions. The proposed framework shows intentional performance in computational cost, accuracy and visualization compared to currently prevalent methods, and has the potential for generalization to model flow fields and corresponding clinical metrics within vessels at different locations. We expect our framework to push the 4D hemodynamic predictions to the real-time level, and in statistically significant fashion, applicable to morphologically variable vessels.

The Multiomics Response of Bacillus subtilis to Simultaneous Genetic and Environmental Perturbations.

How bacteria respond at the systems level to both genetic and environmental perturbations imposed at the same time is one fundamental yet open question in biology. Bioengineering or synthetic biology provides an ideal system for studying such responses, as engineered strains always have genetic changes as opposed to wildtypes and are grown in conditions which often change during growth for maximal yield of desired products. So, engineered strains were used to address the outstanding question. Two Bacillus subtilis strains (MT1 and MT2) were created previously for the overproduction of N-acetylglucosamine (GlcNAc), which were grown in an environment with a carbon shift from glucose to glucose and xylose in the same culture system. We had four groups: (1) a wildtype (WT) grown with glucose at t1; (2) a WT with glucose and xylose at t2; (3) a mutant (MT1) grown with glucose at t1; and (4) MT1 with glucose and xylose at t2. By measuring transcriptomes and metabolomes, we found that GlcNAc-producing mutants, particularly MT2, had a higher yield of N-acetylglucosamine than WT but displayed a smaller maximum growth rate than the wildtype, despite MT1 reaching higher carrying capacity. Underlying the observed growth, the engineered pathways leading to N-acetylglucosamine had both higher gene expression and associated metabolite concentrations in MT1 than WT at both t1 and t2; in bioenergetics, there was higher energy supply in terms of ATP and GTP, with the energy state metric higher in MT1 than WT at both timepoints. Additionally, most top key precursor metabolites were equally abundant in MT1 and WT at either timepoints. Besides that, one prominent feature was the high consistency between transcriptomics and metabolomics in revealing the response. First, both metabolomes and transcriptomes revealed the same PCA clusters of the four groups. Second, we found that the important functions enriched both by metabolomes and transcriptomes overlapped, such as amino acid metabolism and ABC transport. Strikingly, these functions overlapped those enriched by the genes showing a high (positive or negative) correlation with metabolites. Furthermore, these functions also overlapped the enriched KEGG pathways identified using weighted gene coexpression network analysis. All these findings suggest that the responses to simultaneous genetic and environmental perturbations are well coordinated at the metabolic and transcriptional levels: they rely heavily on bioenergetics, but core metabolism does not differ much, while amino acid metabolism and ABC transport are important. This serves as a design guide for bioengineering, synthetic biology, and systems biology.

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.

Elongation of the proximal descending thoracic aorta and associated hemodynamics increase the risk of acute type B aortic dissection.

BACKGROUND: Acute type B aortic dissection (ATBAD) is a life-threatening aortic disease. However, little information is available on predicting and understanding of ATBAD. OBJECTIVE: The study sought to explore the underlying mechanism of ATBAD by analyzing the morphological and hemodynamic characteristics related to aortic length. METHODS: The length and tortuosity of the segment and the whole aorta in the ATBAD group (n= 163) and control group (n= 120) were measured. A fixed anatomic landmark from the distal of left subclavian artery (LSA) to the superior border of sixth thoracic vertebra was proposed as the proximal descending thoracic aorta (PDTA), and the dimensionless parameter, length ratio, was introduced to eliminate the individual differences. The significant morphological parameters were filtrated and the associations between parameters were investigated using statistical approaches. Furthermore, how aortic morphology influenced ATBAD was explored based on idealized aortic models and hemodynamic-related metrics. RESULTS: The PDTA length was significantly increased in the ATBAD group compared with the control group and had a strong positive correlation with the whole aortic length (r= 0.89). The length ratio (LR2) and tortuosity (T2) of PDTA in the ATBAD group were significantly increased (0.15 ± 0.02 vs 0.12 ± 0.02 and 1.73 ± 0.48 vs 1.50 ± 0.36; P< 0.001), and LR2 was positive correlation with T2 (r= 0.73). In receiver-operating curve analysis, the area under the curve was 0.835 for LR2 and 0.641 for T2. Low and oscillatory shear (LOS) was positive correlation with LR2, and the elevated LOS occurred in the distal of LSA. CONCLUSION: Elongation of PDTA is associated with ATBAD, and the length ratio is a novel predictor. Elongated PDTA induced more aggressive hemodynamic forces, and high LOS regions may correspond to the entry tear location. The synergy of the morphological variation and aggressive hemodynamics creates contributory conditions for ATBAD.