Self-supervised tomographic image noise suppression via residual image prior network.

Computed tomography (CT) denoising is a challenging task in medical imaging that has garnered considerable attention. Supervised networks require a lot of noisy-clean image pairs, which are always unavailable in clinical settings. Existing self-supervised algorithms for suppressing noise with paired noisy images have limitations, such as ignoring the residual between similar image pairs during training and insufficiently learning the spectrum information of images. In this study, we propose a Residual Image Prior Network (RIP-Net) to sufficiently model the residual between the paired similar noisy images. Our approach offers new insights into the field by addressing the limitations of existing methods. We first establish a mathematical theorem clarifying the non-equivalence between similar-image-based self-supervised learning and supervised learning. It helps us better understand the strengths and limitations of self-supervised learning. Secondly, we introduce a novel regularization term to model a low-frequency residual image prior. This can improve the accuracy and robustness of our model. Finally, we design a well-structured denoising network capable of exploring spectrum information while simultaneously sensing context messages. The network has dual paths for modeling high and low-frequency compositions in the raw noisy image. Additionally, context perception modules capture local and global interactions to produce high-quality images. The comprehensive experiments on preclinical photon-counting CT, clinical brain CT, and low-dose CT datasets, demonstrate that our RIP-Net is superior to other unsupervised denoising methods.

Inequities in human papillomavirus vaccination among children aged 9-14 years old under constrained vaccine supply in China.

BACKGROUND: Inequities in access to human papillomavirus (HPV) vaccine are becoming a growing critical issue globally. Few studies investigate the factors determining HPV vaccine uptake disparities when vaccine supply is constrained, especially in low- and middle-income countries. The aim of this study was to investigate inequities of HPV vaccination and related factors under the constrained vaccine supply in China. METHODS: A cross-sectional survey was conducted in a developed eastern coastal province and a developing western one in China between November and December 2022. Employing multistage stratified cluster random sampling, the study collected data from parents of children aged 9-14. Mixed-effects logistic regression models with school units as random effects were used for analysis. RESULTS: From 4,127 eligible parents (as vaccine decision makers for girls), 1,346 (32.6%) intended to vaccinate their daughters against HPV, of which 836 (62.1%) attempted to schedule a vaccination appointment. Only 16.4% succeeded in booking an appointment. More than half of the intended parents expected the imported 9-valent HPV vaccine. There were significant disparities in HPV vaccine awareness, intention, and vaccination behavior across educational, income, geographic, ethnic, gender, and health literacy levels. Vaccine awareness and intentions were higher among parents with higher socioeconomic status; however, girls from lower socioeconomic families were more likely to receive the HPV vaccine and had a higher domestically produced vaccination rate. Significant disparities exist in vaccination intentions and actual vaccination behaviors, primarily due to large supply constraints of the HPV vaccine. CONCLUSIONS: Sustained health education campaigns are needed to raise awareness of the HPV vaccine, improve health literacy, and decrease over-preference for the 9-valent HPV vaccine. A mother's HPV vaccination behavior was positively associated with increased intention and actual vaccination behavior for her daughter. This study advocates for complementary cervical cancer prevention programs targeting both mothers and daughters.

A Review on Commercial Oligonucleotide Drug Products.

Oligonucleotide drug products commercially approved in the US and the EU are reviewed. A total of 20 products that includes 1 aptamer, 12 antisense oligonucleotides (ASOs), 6 small interfering ribonucleic acids (siRNAs), and 1 mixture of single-stranded and double-stranded polydeoxyribonucleotides have been identified. A typical oligonucleotide formulation is composed of an oligonucleotide with buffering agent(s), pH adjusting agents, and a tonicity adjusting agent. All the products are presented as 2.1 - 200 mg/mL solutions at pH between 6 and 8.7. Majority of the products are approved for intravenous (IV) and subcutaneous (SC) routes, with two for intravitreal (IVT), two for intrathecal (IT), and one for intramuscular (IM) routes. The primary packaging includes vials and prefilled syringes (PFS). Products approved for IV and IT administration routes and requiring >1.5 mL dose volumes are supplied in vials, while those approved for SC, IM, and IVT and requiring ≤1.5 mL dose volume are supplied in PFS. Based on the compiled dataset, we propose a generalized starting point for an oligonucleotide formulation during early phase development for IV, SC, and IT administration routes. Overall, we believe this harmonized evaluation and understanding of various oligonucleotide drug product attributes will help derive platform generalizations and allows for accelerated early phase development for first-in-human studies.

High-SNR mid-infrared dual-comb spectroscopy using active phase control cooperating with CWs-dependent phase correction.

Mid-infrared (MIR) dual-comb spectroscopy (DCS) is a highly effective method for molecular metrology of rovibrational transition spectra in a quick accurate manner. However, due to limited comb frequency instability, manipulating coherence between two frequency combs to accomplish high-quality spectral analysis in the MIR region is a huge challenge. Here, we developed a comb-teeth resolved MIR DCS based on active phase control cooperating with a CWs-dependent (CWD) interferogram timing correction. Firstly, four meticulously engineered actuators were individually integrated into two near-infrared (NIR) seed combs to facilitate active coherence maintenance. Subsequently, two PPLN waveguides were adopted to achieve parallel difference frequency generations (DFG), directly achieving a coherent MIR dual-comb spectrometer. To improve coherence and signal-to-noise ratio (SNR), a CWD resampled interferogram timing correction was used to optimize the merit of DCS from 7.5 × 105 to 2.5 × 106. Meanwhile, we carried out the measurement of MIR DCS on the methane hot-band absorption spectra (v3 band), which exhibited a good agreement with HITRAN by a standard deviation on recording residual of 0.76%. These experimental results confirm that this MIR DCS with CWD interferogram timing correction has significant potential to characterize the rovibrational transitions of MIR molecules.

Multi-channel Optimization Generative Model for Stable Ultra-Sparse-View CT Reconstruction.

Score-based generative model (SGM) has risen to prominence in sparse-view CT reconstruction due to its impressive generation capability. The consistency of data is crucial in guiding the reconstruction process in SGM-based reconstruction methods. However, the existing data consistency policy exhibits certain limitations. Firstly, it employs partial data from the reconstructed image of iteration process for image updates, which leads to secondary artifacts with compromising image quality. Moreover, the updates to the SGM and data consistency are considered as distinct stages, disregarding their interdependent relationship. Additionally, the reference image used to compute gradients in the reconstruction process is derived from intermediate result rather than ground truth. Motivated by the fact that a typical SGM yields distinct outcomes with different random noise inputs, we propose a Multi-channel Optimization Generative Model (MOGM) for stable ultra-sparse-view CT reconstruction by integrating a novel data consistency term into the stochastic differential equation model. Notably, the unique aspect of this data consistency component is its exclusive reliance on original data for effectively confining generation outcomes. Furthermore, we pioneer an inference strategy that traces back from the current iteration result to ground truth, enhancing reconstruction stability through foundational theoretical support. We also establish a multi-channel optimization reconstruction framework, where conventional iterative techniques are employed to seek the reconstruction solution. Quantitative and qualitative assessments on 23 views datasets from numerical simulation, clinical cardiac and sheep's lung underscore the superiority of MOGM over alternative methods. Reconstructing from just 10 and 7 views, our method consistently demonstrates exceptional performance.

Spectrum learning for super-resolution tomographic reconstruction.

Objective. Computed Tomography (CT) has been widely used in industrial high-resolution non-destructive testing. However, it is difficult to obtain high-resolution images for large-scale objects due to their physical limitations. The objective is to develop an improved super-resolution technique that preserves small structures and details while efficiently capturing high-frequency information.Approach. The study proposes a new deep learning based method called spectrum learning (SPEAR) network for CT images super-resolution. This approach leverages both global information in the image domain and high-frequency information in the frequency domain. The SPEAR network is designed to reconstruct high-resolution images from low-resolution inputs by considering not only the main body of the images but also the small structures and other details. The symmetric property of the spectrum is exploited to reduce weight parameters in the frequency domain. Additionally, a spectrum loss is introduced to enforce the preservation of both high-frequency components and global information.Main results. The network is trained using pairs of low-resolution and high-resolution CT images, and it is fine-tuned using additional low-dose and normal-dose CT image pairs. The experimental results demonstrate that the proposed SPEAR network outperforms state-of-the-art networks in terms of image reconstruction quality. The approach successfully preserves high-frequency information and small structures, leading to better results compared to existing methods. The network's ability to generate high-resolution images from low-resolution inputs, even in cases of low-dose CT images, showcases its effectiveness in maintaining image quality.Significance. The proposed SPEAR network's ability to simultaneously capture global information and high-frequency details addresses the limitations of existing methods, resulting in more accurate and informative image reconstructions. This advancement can have substantial implications for various industries and medical diagnoses relying on accurate imaging.

Iterative Residual Optimization Network for Limited-Angle Tomographic Reconstruction.

Limited-angle tomographic reconstruction is one of the typical ill-posed inverse problems, leading to edge divergence with degraded image quality. Recently, deep learning has been introduced into image reconstruction and achieved great results. However, existing deep reconstruction methods have not fully explored data consistency, resulting in poor performance. In addition, deep reconstruction methods are still mathematically inexplicable and unstable. In this work, we propose an iterative residual optimization network (IRON) for limited-angle tomographic reconstruction. First, a new optimization objective function is established to overcome false negative and positive artifacts induced by limited-angle measurements. We integrate neural network priors as a regularizer to explore deep features within residual data. Furthermore, the block-coordinate descent is employed to achieve a novel iterative framework. Second, a convolution assisted transformer is carefully elaborated to capture both local and long-range pixel interactions simultaneously. Regarding the visual transformer, the multi-head attention is further redesigned to reduce computational costs and protect reconstructed image features. Third, based on the relative error convergence property of the convolution assisted transformer, a mathematical convergence analysis is also provided for our IRON. Both numerically simulated and clinically collected real cardiac datasets are employed to validate the effectiveness and advantages of the proposed IRON. The results show that IRON outperforms other state-of-the-art methods.

Protective activity of Malus doumeri leaf extract on H2O2-induced oxidative injury in H9C2 rat cardiomyocytes.

In this study, Malus doumeri leaf extract (MDLE) was used to test its anti-oxidation capacity in vitro, it has been preliminarily analyzed for H2O2-induced oxidative damage in H9C2 cells and its main active components. The antioxidant capacity through DPPH (1, 1-Diphenyl-2-Picrylhydrazyl), ABTS+• [2,2,2'-azino-BIS-(3-ethylbenzo-thiazoline-6-sulfonic acid)] radical ion, •OH (hydroxyl radical), and • O 2 - (superoxide anion) were determined in vitro. The proliferation of H9C2 cells was examined by MTT [3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-Tetrazolium bromide]. MDA (malondialdehyde), SOD (superoxide dismutase), CAT (catalase), GSH (glutathione), and GSH-Px (glutathione peroxidase) were determined by colorimetry. Apoptosis induced by oxidative damage was detected by flow cytometry. The mRNA expression of antioxidant related genes of SOD, CAT, GSH, and GSH-Px were checked by qRT-PCR (quantitative real-time polymerase chain reaction). The MDLE main active components were analyzed by HPLC (high-performance liquid chromatography). MDLE had significant scavenging effects on DPPH, ABTS+•, •OH, and superoxide anion radicals in a concentration-dependent manner. H2O2 treatment could significantly lead to oxidative stress injury of H9C2 cells, and MDLE treatment significantly improved the degree of H9C2 cell damage, and showed a positive correlation with concentration. MDLE can also reduce apoptosis caused by oxidative damage. MDLE treatment could significantly reduce MDA content and increase CAT, SOD, GSH, and GSH-Px contents and expression. In addition, by HPLC analysis, the following six bioactive components were detected from MDLE: chlorogenic acid, isoquercitrin, quercetin, baicalin, and phloretin. Therefore, MDLE has a good protective effect on myocardial cells.

A Novel PD-L1-Containing MSLN Targeting Vaccine for Lung Cancer Immunotherapy.

Therapeutic tumor vaccines have become an important breakthrough in the treatment of various solid tumors including lung cancer. Dendritic cells (DCs)-based tumor vaccines targeting tumor-associated antigens (TAAs) play a key role in immunotherapy and immunoprevention. However, the weak immunogenicity of TAAs and low immune response rates are a major challenge faced in the application of therapeutic tumor vaccines. Here, we tested whether targeting an attractive target Mesothelin (MSLN) and PD-L1 immune checkpoint molecule to DCs in vivo would elicit therapeutic antitumor cytotoxic T lymphocyte (CTL) response. We generated specific MSLN fragment combined with PD-L1 and GM-CSF peptide immunogen (MSLN-PDL1-GMCSF) based on the novel anti-PD-L1 vaccination strategy we recently developed for the cancer treatment and prevention. We found that DCs loaded with MSLN-PDL1-GMCSF vaccine elicited much stronger endogenous anti-PD-L1 antibody and T cell responses in immunized mice and that antigen specific CTLs had cytolytic activities against tumor cells expressing both MSLN and PD-L1. We demonstrated that vaccination with MSLN-PDL1-GMCSF potently inhibited the tumor growth of MSLN+ and PD-L1+ lung cancer cells, exhibiting a significant therapeutic anti-tumor potential. Furthermore, PD-1 blockade further improved the synergistic antitumor therapeutic efficacy of MSLN-PDL1-GMCSF vaccine in immunized mice. In summary, our data demonstrated for the first time that this PD-L1-containing MSLN therapeutic vaccine can induce persistent anti-PD-L1 antibody and CTL responses, providing an effective immunotherapeutic strategy for lung cancer immunotherapy by combining MSLN-PDL1-GMCSF vaccine and PD-1 blockade.

Single-cell transcriptomes identifies characteristic features of mouse macrophages in liver Mallory-Denk bodies formation.

Mallory-Denk bodies (MDBs) consist of intracellular aggregates of misfolded proteins in ballooned hepatocytes and serve as important markers of progression in certain liver diseases. Resident hepatic macrophage-mediated inflammation influences the development of chronic liver diseases and cancer. Here, the first systematic study of macrophages heterogeneity in mice was conducted to illustrate the pathogenesis of MDB formation using single-nucleus RNA sequencing (snRNA-seq). Furthermore, we provided transcriptional profiles of macrophages obtained from the fractionation of mouse liver tissues following chronic injury. We equally identified seven discrete macrophage subpopulations, each involved in specific cellular activated pathways such as basal metabolism, immune regulation, angiogenesis, and cell cycle regulation. Among these, a specific macrophage cluster (Cluster4), a subpopulation specifically expressing genes that regulate cell division and the cell cycle, was identified. Interestingly, we found that CCR2 was significantly induced in Cluster2, thereby inducing monocytes to migrate to macrophages to promote MDB pathogenesis. Thus, our study is the first to demonstrate the heterogeneity of macrophages associated with liver MDB formation in mice through single-cell resolution. This serves as the basis for further insights into the pathogenesis of liver MDB formation and molecular mechanisms of chronic liver disease progression.

A Novel Therapeutic Tumor Vaccine Targeting MUC1 in Combination with PD-L1 Elicits Specific Anti-Tumor Immunity in Mice.

Dendritic cells (DCs), as professional antigen-presenting cells (APCs), play a key role in the initiation and regulation of humoral and cellular immunity. DC vaccines loaded with different tumor-associated antigens (TAAs) have been widely used to study their therapeutic effects on cancer. A number of clinical trials have shown that DCs are safe as an antitumor vaccine and can activate certain anti-tumor immune responses; however, the overall clinical efficacy of DC vaccine is not satisfactory, so its efficacy needs to be enhanced. MUC1 is a TAA with great potential, and the immune checkpoint PD-L1 also has great potential for tumor treatment. Both of them are highly expressed on the surface of various tumors. In this study, we generated a novel therapeutic MUC1-Vax tumor vaccine based on the method of PD-L1-Vax vaccine we recently developed; this novel PD-L1-containing MUC1-Vax vaccine demonstrated an elevated persistent anti-PD-L1 antibody production and elicited a much stronger protective cytotoxic T lymphocyte (CTL) response in immunized mice. Furthermore, the MUC1-Vax vaccine exhibited a significant therapeutic anti-tumor effect, which significantly inhibited tumor growth by expressing a high MUC1+ and PD-L1+ level of LLC and Panc02 tumor cells, and prolonged the survival of cancer-bearing animals. Taken together, our study provides a new immunotherapy strategy for improving the cross-presentation ability of therapeutic vaccine, which may be applicable to pancreatic cancer, lung cancer and for targeting other types of solid tumors that highly express MUC1 and PD-L1.

Multi-domain integrative Swin transformer network for sparse-view tomographic reconstruction.

Decreasing projection views to a lower X-ray radiation dose usually leads to severe streak artifacts. To improve image quality from sparse-view data, a multi-domain integrative Swin transformer network (MIST-net) was developed and is reported in this article. First, MIST-net incorporated lavish domain features from data, residual data, image, and residual image using flexible network architectures, where a residual data and residual image sub-network was considered as a data consistency module to eliminate interpolation and reconstruction errors. Second, a trainable edge enhancement filter was incorporated to detect and protect image edges. Third, a high-quality reconstruction Swin transformer (i.e., Recformer) was designed to capture image global features. The experimental results on numerical and real cardiac clinical datasets with 48 views demonstrated that our proposed MIST-net provided better image quality with more small features and sharp edges than other competitors.

Collaboration on evidence synthesis in Africa: a network study of growing research capacity.

BACKGROUND: Evidence-based practice in medicine and social policy relies heavily on evidence synthesis. To translate evidence into practical guidelines for low- and middle-income countries, local expertise is essential. The objectives of this study are to assess the change in capacity for conducting evidence synthesis in Africa and to identify key African institutions for regional capacity-building. We take on a network perspective, considering that the position of an institution in the African evidence ecosystem is one constituent of its research capacity. METHODS: We systematically identified 3548 evidence synthesis publications between 2008 and 2019 with at least one author in Africa from the Web of Science Core Collection. These articles involved 3769 institutions. Longitudinal institution-level collaboration network data were constructed based on co-authorship information. We used social network analysis to examine the institutions' connectivity and tendency for intra- and interregional collaboration. We also identified the degree- and betweenness-central African institutions and explored the structure and composition of their local network neighbourhoods. RESULTS: The number of African institutions involved in evidence synthesis has increased substantially over the last decade, from 31 in 2008 to 521 in 2019, and so has the number of evidence synthesis publications with authors in Africa. African institutions in the evidence ecosystem have also become more connected during this period. Although the amount of intercontinental collaboration continues to exceed that of regional collaboration, the tendency for African institutions to collaborate with partners in Africa is increasing. We identified seven institutions-in South Africa, Egypt and Uganda-as central to the collaboration networks between 2008 and 2019, all of whom showed a tendency to collaborate across sectors. CONCLUSION: The development of more regionally based network-building initiatives would help to foster communities of practice and inter-institutional collaboration, strengthening regional research capacity. Moreover, the analysis in this study adds depth beyond a simple bibliometric analysis and illustrates that network analysis could provide a useful tool to evaluate the effectiveness of capacity-building strategies and programmes in the future.

Altered regulation of LncRNA analysis of human alcoholic hepatitis with Mallory-Denk Bodies (MDBs) is revealed by RNA sequencing.

Mallory-Denk Bodies (MDBs) are prevalent in a variety of liver diseases including alcoholic hepatitis (AH) and are formed in mice livers by feeding DDC. Long noncoding RNAs (lncRNAs) are considered as emerging new gene regulators, which participates in many functional activities through diverse mechanisms. We previously reported the mechanisms involved in the formation of liver MDBs in mouse model and in AH livers where MDBs had formed. To investigate the regulation of mRNAs expression and the probable role of lncRNAs in AH livers with MDBs, RNA-Seq analyses was further conducted to determine the mRNA and lncRNA expression profiles of the AH livers compared with the normal livers. It showed that different lncRNAs have different information contribution degrees by principal component analysis, and the integrated analysis of lncRNA-mRNA co-expression networks were linked to endocytosis, cell cycle, p53 signaling pathways in the human. Based on the co-expression networks, we identify 36 mRNAs that could be as potential biomarkers of alcoholic liver disease (ALD) and hepatocellular carcinoma (HCC). To our knowledge, this is the first report on the regulatory network of lncRNAs associated with liver MDB formation in human, and these results might offer new insights into the molecular mechanisms of liver MDB formation and the progression of AH to HCC.

Charge reversible hyaluronic acid-modified dendrimer-based nanoparticles for siMDR-1 and doxorubicin co-delivery.

Dendrimer-based nanoparticles have shown promising applications in delivery of small interference RNA (siRNA) to downregulate proteins that contribute to multidrug resistance (MDR). Various types of modification can further enhance the anti-tumor efficacy of dendrimer-based nanoparticles. In this study, generation 4 polyamodoamine (PAMAM) was conjugated with PEG2k-DOPE. The PAMAM-PEG2k-DOPE co-polymer, together with mPEG2k-DOPE, was formulated into mixed dendrimer micelles (MDMs) that can complex siRNA through the cationic PAMAM moieties and encapsulate hydrophobic drug in the micellar lipid cores. DOPE-conjugated hyaluronic acid (HA) was coated on the surface of MDMs to shield the exposed positive charge on PAMAM and to increase the cellular association with CD44+ cancer cells. The HA-modified MDMs could form stable complexes with siRNA, prevent RNase-mediated siRNA degradation and maintain its integrity. Cellular association and cytotoxicity of HA-modified MDMs were investigated in A2780 ADR, MDA-MB-231 and HCT 116 cell lines. The HA-modified MDMs alleviated the toxicity from cationic charge, increase the cancer cell specificity and enhance the cancer cell killing effect in CD44+ cell line.

Recent advancements in liposome technology.

The liposomes have continued to be well-recognized as an important nano-sized drug delivery system with attractive properties, such a characteristic bilayer structure assembling the cellular membrane, easy-to-prepare and high bio-compatibility. Extensive effort has been devoted to the development of liposome-based drug delivery systems during the past few decades. Many drug candidates have been encapsulated in liposomes and investigated for reduced toxicity and extended duration of therapeutic effect. The liposomal encapsulation of hydrophilic and hydrophobic small molecule therapeutics as well as other large molecule biologics have been established among different academic and industrial research groups. To date, there has been an increasing number of FDA-approved liposomal-based therapeutics together with more and more undergoing clinical trials, which involve a wide range of applications in anticancer, antibacterial, and antiviral therapies. In order to meet the continuing demand for new drugs in clinics, more recent advancements have been investigated for optimizing liposomal-based drug delivery system with more reproducible preparation technique and a broadened application to novel modalities, including nucleic acid therapies, CRISPR/Cas9 therapies and immunotherapies. This review focuses on the recent liposome' preparation techniques, the excipients of liposomal formulations used in various novel studies and the routes of administration used to deliver liposomes to targeted areas of disease. It aims to update the research in liposomal delivery and highlights future nanotechnological approaches.

Folate targeted lipid chitosan hybrid nanoparticles for enhanced anti-tumor efficacy.

Folic acid is often used for active targeting of tumor cells to enhance therapeutic outcomes. Here, folic acid was conjugated with chitosan and folate-conjugated chitosan-lipid hybrid nanoparticles were prepared by ionic gelation method using anionic lipid. These nanoparticles were in size range of 200 to 400 nm with spherical shape. In vitro drug release data suggested a sustained release of cisplatin. The therapeutic efficacy of the folate-conjugated hybrid nanoparticles was evaluated in SK-OV-3, A2780 and MCF-7 cancer cell lines. A significant increase in cytotoxicity was observed with folate targeted LPHNPs compared to non-targeted LPHNPs. Significantly enhanced cellular uptake and cell cycle arrest resulting from folate-targeted nanoparticles were confirmed using fluorescence microscopy and flow cytometry. The therapeutic efficacy and tumor penetration were further evaluated in 3D spheroid tumor models. These studies suggest that folate-conjugated lipid-chitosan nanoparticles could enhance therapeutic activity and may represent a promising platform for active targeting of tumor cells.

Monoclonal Antibody 2C5-Modified Mixed Dendrimer Micelles for Tumor-Targeted Codelivery of Chemotherapeutics and siRNA.

Targeted delivery of chemotherapeutics to tumors has the potential to reach a high dose at the tumor while minimizing systemic exposure. Incorporation of antibody within a micellar platform represents a drug delivery system for tumor-targeted delivery of antitumor agents. Such modified immunomicelles can result in an increased accumulation of antitumor agents and enhanced cytotoxicity toward cancer cells. Here, mixed dendrimer micelles (MDM) composed of PEG2k-DOPE-conjugated generation 4 polyamidoamine dendrimer G4-PAMAM-PEG2k-DOPE and PEG5k-DOPE were coloaded with doxorubicin and siMDR-1. This formulation was further modified with monoclonal antibodies 2C5 with nucleosome-restricted specificity that effectively recognized cancer cells via the cell-surface-bound nucleosomes. Micelles with attached 2C5 antibodies significantly enhanced cellular association and tumor killing in both monolayer and spheroid tumor models as well as in vivo in experimental animals compared to the nontargeted formulations.

Lipid-chitosan hybrid nanoparticles for controlled delivery of cisplatin.

Lipid-polymer hybrid nanoparticles (LPHNP) are delivery systems for controlled drug delivery at tumor sites. The superior biocompatible properties of lipids and structural advantages of polymers can be obtained using this system for controlled drug delivery. In this study, cisplatin-loaded lipid-chitosan hybrid nanoparticles were formulated by the single step ionic gelation method based on ionic interaction of positively charged chitosan and negatively charged lipid. Formulations with various chitosan to lipid ratios were investigated to obtain the optimal particle size, encapsulation efficiency, and controlled release pattern. Transmission electron microscope and dynamic light scattering analysis demonstrated a size range of 181-245 nm and a zeta potential range of 20-30 mV. The stability of the formulation was demonstrated by thermal studies. Cytotoxicity and cellular interaction of cisplatin-loaded LPHNP were investigated using in vitro cell-based assays using the A2780 ovarian carcinoma cell line. The pharmacokinetics study in rabbits supported a controlled delivery of cisplatin with enhanced mean residence time and half-life. These studies suggest that cisplatin loaded LPHNP have promise as a platform for controlled delivery of cisplatin in cancer therapy.

Surface-engineered polyethyleneimine-modified liposomes as novel carrier of siRNA and chemotherapeutics for combination treatment of drug-resistant cancers.

Modification of nanoparticle surfaces with PEG has been widely considered the gold standard for many years. However, PEGylation presents controversial and serious challenges including lack of functionality, hindered cellular interaction, allergic reactions, and stimulation of IgM production after repetitive dosing that accelerates blood clearance of the nanoparticles. We report the development of novel liposomal formulations surface-modified with a low molecular weight, branched polyethyleneimine (bPEI)-lipid conjugate for use as an alternative to PEG. The formulations had very good stability characteristics in ion- and protein-rich mediums. Protein adsorption onto the liposomal surface did not interfere with the cellular interaction. bPEI-modified liposomes (PEIPOS) showed enhanced association with three different cell lines by up to 75 times compared to plain or PEGylated liposomes and were without carrier toxicity. They also penetrated the deeper layers of 3D spheroids. Encapsulating paclitaxel (PTX) into PEIPOS did not change its main mechanism of action. PEIPOS complexed and intracellularly delivered siRNAs and downregulated resistance-associated proteins. Finally, tumor growth inhibition was observed in a mouse ovarian xenograft tumor model, without signs of toxicity, in animals treated with the siRNA/PTX co-loaded formulation. These complex-in-nature but simple-in-design novel liposomal formulations constitute viable and promising alternatives with added functionality to their PEGylated counterparts.