Functional Evaluation of 3D Liver Models Labeled with Polysaccharide Functionalized Magnetic Nanoparticles.

Objective: To study the segment of liver according to the large amount of three-dimensional(3D) reconstructive images of normal human livers and the vascular system, and to recognize the basic functional liver unit based on the anatomic features of the intrahepatic portal veins. Methods: The enhanced CT primitive DICOM files of 1 260 normal human livers from different age groups who treated from October 2013 to February 2017 provided by 16 hospitals were analyzed using the computer-aided surgery system.The 3D liver and liver vascular system were reconstructed, and the digital liver 3D model was established.The vascular morphology, anatomical features, and anatomical distributions of intrahepatic portal veins were statistically analyzed. Results: The digital liver model obtained from the 3D reconstruction of CAS displayed clear intrahepatic portal vein vessels of level four.Perform a digital liver segments study based on the analysis of level four vascular distribution areas.As the less anatomical variation of left hepatic portal vein, the liver was classified into four types of liver segmentation mainly based on right hepatic portal vein.Type A was similar to Couinaud or Cho's segmentation, containing 8 segments(537 cases, 42.62%). Type B contained 9 segments as there are three ramifications of right-anterior portal vein(464 cases, 36.82%). The main difference for Type C was the variation of right-posterior portal vein which was sector shape(102 cases, 8.10%). Type D contained the cases with special portal vein variations, which needs three-dimensional simulation to design individualized liver resection plan(157 cases, 12.46%). These results showed that there was no significant difference in liver segmental typing between genders(χ(2)=2.179, P=0.536) and did not reveal any significant difference in liver segmental typing among the different age groups(χ(2)=0.357, P=0.949). Conclusions: The 3D digital liver model can demonstrate the true 3D anatomical structures, and its spatial vascular variations.The observation of anatomic features, distribution areas of intrahepatic portal veins and individualized liver segmentation achieved via digital medical 3D visualization technology is of great value for understand the complexity of liver anatomy and to guide the precise hepatectomy.

Context: Research on drug delivery carriers that use nanoparticles is currently attracting a great deal of attention. In order to evaluate the safety of these drug carriers for clinical applications, a full assessment of their toxicity and bioactivity is required. Although it is well-known that the surface charge of nanoparticles influences their bioactivity, most of the published studies on n-butylcyanoacrylate (NBCA) nanoparticles as a potential drug delivery carrier are restricted to analyzing the anionic form.Objective: We compared biological responses of cyanoacrylate anionic nanoparticles with cationic nanoparticles in cultured murine macrophages for assessing cytotoxicity and inflammatory responses.Materials and methods: The cytotoxicity was evaluated with the MTS and LDH leakage assays. Inflammatory responses were evaluated by measurement of nitric oxide (NO), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNF-α). The interaction of the nanoparticle and the macrophage was assessed by fluorescence microscopy.Result: Anionic and cationic NP showed no detectable cytotoxicity at a concentration of 10 µg/mL or less. At concentrations greater than 10 µg/mL, cationic NP displayed lower cytotoxicity by comparison with anionic NP. NO, IL-6, and TNF-α production were not induced by anionic or cationic nanoparticles alone. In contrast, both types of nanoparticles decreased NO, IL-6, and TNF-α productions induced by LPS. However, the anti-inflammatory effect of anionic nanoparticles was significantly greater than that of cationic nanoparticles. Nanoparticles were presumed to be either internalized or attached to the cell membranes.Discussion and conclusion: NBCA nanoparticles are not only important as potential drug carriers but also as promising anti-inflammatory agents that may have therapeutic properties.

Many types of nanoparticles (NPs) are tested for use in medical products, particularly in imaging and gene and drug delivery. For these applications, cellular uptake is usually a prerequisite and is governed in addition to size by surface characteristics such as hydrophobicity and charge. Although positive charge appears to improve the efficacy of imaging, gene transfer, and drug delivery, a higher cytotoxicity of such constructs has been reported. This review summarizes findings on the role of surface charge on cytotoxicity in general, action on specific cellular targets, modes of toxic action, cellular uptake, and intracellular localization of NPs. Effects of serum and intercell type differences are addressed. Cationic NPs cause more pronounced disruption of plasma-membrane integrity, stronger mitochondrial and lysosomal damage, and a higher number of autophagosomes than anionic NPs. In general, nonphagocytic cells ingest cationic NPs to a higher extent, but charge density and hydrophobicity are equally important; phagocytic cells preferentially take up anionic NPs. Cells do not use different uptake routes for cationic and anionic NPs, but high uptake rates are usually linked to greater biological effects. The different uptake preferences of phagocytic and nonphagocytic cells for cationic and anionic NPs may influence the efficacy and selectivity of NPs for drug delivery and imaging.

To establish the accuracy of virtual hepatic resection using three-dimensional (3D) models constructed from computed tomography angioportography (CTAP) images in determining the liver volume (LV) resected during resectional liver surgery. The ability to measure LV before surgery could be useful in determining the extent and nature of hepatic resection. Accurate assessment of LV and an estimate of liver function may also allow prediction of postoperative liver failure in patients undergoing resection, assist in volume-enhancing embolization procedures, help with the planning of staged hepatic resection for bilobar disease, and aid in selection of living-related liver donors. A retrospective study was conducted involving 27 patients scheduled for liver resection. Using mapping technology, 3D models were constructed from helical CTAP images. From these 3D models, tumor volume, total LV, and functional LV were calculated and were compared with body weight. The 3D liver models were subjected to a virtual hepatectomy along established anatomical planes, and the resected LV was calculated. The resected volume predicted by radiologists (unaware of the actual weight) was compared with the specimen weight measured after actual surgical resection. A significant correlation was found between body weight and functional LV but not total LV. The computer prediction of resected LV after virtual hepatectomy of 3D models compared well with resected liver weight. Virtual hepatectomy of 3D CTAP reconstructed images provides an accurate prediction of liver mass removed during subsequent hepatic resection. The authors intend to combine this technology with an assessment of liver function to attempt to predict patients at risk for liver failure after hepatic resection.

Hepatocellular Carcinoma (HCC) is the most primary liver tumor and one of the most common cancers worldwide, particularly in developing countries. Various treatment options are available to treat HCC with various degrees of success rate and mortality. Studies done by researchers have shown that pre-surgical planning tools aid surgeons in planning surgery procedures for HCC as well as increasing post-surgery survival rate. Previously, pre-surgical planning was done based on medical images acquired using medical imaging devices such as Computer Tomography (CT), X-Ray, Ultrasound, and Magnetic Resonance Imaging (MRI). Surgeons will need to examine the medical images carefully, and picturing a 3D liver model using imagination. This process is very time consuming, and anatomical variations of tumors might lead to suboptimal treatment strategy decision. This project focuses on the application of virtual reality technology in HCC pre-surgical planning. One of many deployments of virtual reality in pre-surgical planning is to display a virtual 3D liver model which resembles patient's liver. It is built by taking segmented 2D axial slices of patient's liver as input. The operation is done by using surface extraction technique. The product of surface extraction is a virtual 3D mesh, which is consisted of a group of points recorded in their respective three dimensional coordinates. These points are mapped to graphic primitives by graphic renderer. Interaction control with the 3D model is done by using computer hardware interface devices such as mouse, keyboard, joystick or pen input devices.

Among classes of nanoparticles developed as drug carriers and theranostics, nanodiamond (ND) has been gaining an increasing attention owing to its biocompatibility, easy functionalisation and chemical stability. Although biocompatibility studies on nanodiamond produced by detonation technique have been explored extensively, NDs produced by laser assisted technique are yet to be investigated. Here, we present comparative study on toxicity of NDs in 2D and 3D liver models. Results suggest toxicity occurs on the 2D model at higher concentrations of NDs after long term exposure. However, cytotoxic effect was not observed in the case of the 3D model. In addition, alterations in nanomechanical properties of the cells after uptake of NDs were detected by a Lorentz contact resonance (LCR) spectroscopic study. Overall, the results indicate differences in the toxicity profile of NDs in 2D and 3D and long term toxicity studies on NDs produced by laser assisted technique must be done prior to any biomedical applications.

Background and Objectives: Liver fibrosis is the key prognostic factor in patients with chronic liver diseases (CLD). Computed tomography (CT) is widely used in clinical practice, but it has limited value in assessing liver fibrosis in precirrhotic stages. Quantitative CT analysis based on radiomics can provide additional information by extracting hidden image patterns, but the optimal approach remains to be determined. The aims of this study were to evaluate automated CT-based radiomic models for predicting biopsy-proven liver fibrosis, to compare different segmentation strategies and organ inclusions approaches, and to assess its performance against vibration-controlled transient elastography (VCTE). We also examined whether these models could predict liver steatosis. Methods: In this retrospective study, 58 patients with biopsy-proven CLD and 9 controls underwent VCTE and contrast-enhanced abdominal CT within three months of biopsy. Radiomic features were extracted from portal-venous-phase images using both two-dimensional (2D) and three-dimensional (3D) segmentations of the liver, spleen, and combined liver–spleen. Multilayer perceptron neural (MLP) networks were trained to predict fibrosis staging (≥F1, ≥F2, ≥F3, and F4) and steatosis grading (≥S1, ≥S2, and S3). Model performance was assessed using area under the receiver operating characteristic curve (AUROC) and accuracy. Results: The 3D radiomic models outperformed 2D models in predicting liver fibrosis stages. In the 3D radiomic model category, the combined 3D liver–spleen model achieved very good to excellent performance (AUROCs 0.974, 0.929, 0.928, and 0.898, respectively, for ≥F1, ≥F2, ≥F3, and F4), with comparable results to VCTE (AUROCs 0.921, 0.957, 0.968, and 0.909, respectively, for ≥F1, ≥F2, ≥F3, and F4). Radiomic models showed poor predictive ability for steatosis grades (AUROCs 0.44–0.69) compared to controlled attenuation parameter (CAP) (AUROCs 0.798–0.917). Conclusions: CT-based radiomic models showed potential for predicting liver fibrosis stage. The 3D model of liver and spleen had the highest performance, comparable to VCTE. This approach could be valuable in clinical settings where elastography is unavailable or inconclusive and for opportunistic screening in patients already undergoing CT for other medical indications. In contrast, portal-venous-phase radiomics lacked predictive value for steatosis assessment. Larger, multicenter studies are required to validate these results.

Evaluation of an innovative three-dimensional liver model

With the emergence of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), three-dimensional images facilitate the generation of 3D models of a patient, providing a new practical and accurate assistance, particularly for surgical planning. These images can be manipulated to produce an accurate 3D representation of an organ. The reconstructed mesh can be used to generate and visualize a deformable model during surgical intervention using Augmented Reality (AR) technology. To obtain an efficient reconstruction, a segmentation of these medical images using deep learning architecture can be used to extract the target organ's properties. Many methods were proposed based on the captured pre-operative patient's CT scans. Generally, the segmentation process is done manually using image processing software. In this context several approaches were proposed, these methods are not efficient and need human interaction to select the segmentation area correctly. This work aims to develop a deep learning method using a Convolutional Neural Network (CNN) that captures the liver organ from a set of CT scans. Given preoperative patient-specific data (CT scans), the U-net architecture is implemented to detect the liver organ. As a result, the segmented 2D images are used to generate a 3D patient-specific liver model.

Lower hepatotoxicity risk in Xelaglifam, a novel GPR40 agonist, compared to Fasiglifam for type 2 diabetes therapy

S. pneumoniae is one of the most significant human pathogens, causing high morbidity and mortality rates globally. Although there are vaccine available such as PPV 23, PCV7, PCV10, and PCV13, they are ineffective in some situations due to the differing epidemiology of various serotypes depending on the site of infection and the geographical location. Furthermore, they are expensive to produce and distribute. Universal research is presently concentrated on establishing other pneumococcalvaccine approaches such as using pneumococcal surface protein A (PspA) which relate to pathogenesis and are common to all serotypes. In this study polymeric nanoparticles (NPs) encapsulating PspA4Pro were incorporated into microcarriers using L-leucine and spray dried to produce nanocomposite micro#particles (NCMPs) dry powder for inhalation. Parameters for the preparation of protein-loaded polyester poly (Glycerol Adipate-co-I‰-Pentadecalactone), (PGA-co-PDL) NCMPs were optimised using Taguchi design and BSA as a model protein, by the double emulsion solvent evaporation method followed by spray drying. Particle size was mainly affected by the polymer mass and small particle size ≤ 500nm was achieved. The most important factor for obtaining a high BSA loading was BSA concentration. The spray drying process was optimised to produce NCMPs with a porous corrugated surface, 50% yield, MMAD of 1.71±0.10 I¼m and FPF% of 78.57±0.1%. Adsorption of chitosan hydrochloride (CHL) onto PGA-co-PDL NPs can be used assuccessful strategies to produce cationic NPs. Cationic NPs were prepared with similarparticle size to anionic NPs ≤ 500nm. The In vitro aerosolisation performance ofcationic NPs/NCMPs showed FPF% of 46.79±11.21% and MMAD of 1.49±0.29 I¼m. Further cell viability studies on A549 cell line showed a good profile with a cell viability of 79±4.7% for anionic NPs/NCMPs and 78.85±9.96% for cationic xviii NPs/NCMPs at 2.5 mg/ml concentration after 24 h exposure. The previous results introduced a successful method for preparing anionic and cationic NPs/NCMPs for delivering PspA4Pro as dry powder via inhalation. The particle size of PspAPro4 loaded anionic NPs and cationic NPs were 310±25.3 nm and 409.7±49.5 nm, respectively, to be effectively taken up by dendritic cells (DCs). The PspA4Pro loading in anionic NPs was 65.73±5.6 I¼g/mg and in cationic NPs was 9.84±1.4 I¼g/mg. The PspA4Pro released from anionic and cationic NPs/NCMPs preserved its primary and secondary structure as evaluated by SDS-PAGE and circular dichroism. In vitro release studies showed that the anionic NPs/NCMPs formulations achieved a cumulative release of 21.01±1.5% while the cationic NPs/NCMPs formulation released 83.13 ±0.84% after 48 h. DCs uptake studies provide evidence of particles uptake by DCs upon incubation for 1 h as visualized by confocal microscopy. These results indicate the use of optimised methods for developing polymeric based NCMPs for vaccine delivery via inhalation against pneumococcal diseases.

Pulmonary immunization enhances local humoral and cell-mediated mucosal protection, which are critical for vaccination against lung-specific pathogens such as influenza or tuberculosis. A variety of nanoparticle (NP) formulations have been tested preclinically for pulmonary vaccine development, yet the role of NP surface charge on downstream immune responses remains poorly understood. We used the Particle Replication in Non-Wetting Templates (PRINT) process to synthesize hydrogel NPs that varied only in surface charge and otherwise maintained constant size, shape, and antigen loading. Pulmonary immunization with ovalbumin (OVA)-conjugated cationic NPs led to enhanced systemic and lung antibody titers compared with anionic NPs. Increased antibody production correlated with robust germinal center B-cell expansion and increased activated CD4(+) T-cell populations in lung draining lymph nodes. Ex vivo treatment of dendritic cells (DCs) with OVA-conjugated cationic NPs induced robust antigen-specific T-cell proliferation with ∼ 100-fold more potency than soluble OVA alone. Enhanced T-cell expansion correlated with increased expression of surface MHCII, T-cell coactivating receptors, and key cytokines/chemokine expression by DCs treated with cationic NPs, which were not observed with anionic NPs or soluble OVA. Together, these studies highlight the importance of NP surface charge when designing pulmonary vaccines, and our findings support the notion that cationic NP platforms engender potent humoral and mucosal immune responses.

We developed a medical image segmentation and preoperative planning application which implements a semiautomatic and a hybrid semiautomatic liver segmentation algorithm. The aim of this study was to evaluate the feasibility of computer-assisted liver tumor surgery using these algorithms which are based on thresholding by pixel intensity value from initial seed points. A random sample of 12 patients undergoing elective high-risk hepatectomies at our institution was prospectively selected to undergo computer-assisted surgery using our algorithms (June 2013-July 2014). Quantitative and qualitative evaluation was performed. The average computer analysis time (segmentation, resection planning, volumetry, visualization) was 45 min/dataset. The runtime for the semiautomatic algorithm was <0.2 s/slice. Liver volumetric segmentation using the hybrid method was achieved in 12.9 s/dataset (SD ± 6.14). Mean similarity index was 96.2 % (SD ± 1.6). The future liver remnant volume calculated by the application showed a correlation of 0.99 to that calculated using manual boundary tracing. The 3D liver models and the virtual liver resections had an acceptable coincidence with the real intraoperative findings. The patient-specific 3D models produced using our semiautomatic and hybrid semiautomatic segmentation algorithms proved to be accurate for the preoperative planning in liver tumor surgery and effectively enhanced the intraoperative medical image guidance.

Multi-cellular transitional organotypic models to investigate liver fibrosis

Point-of-use, automated fabrication of a 3D human liver model supplemented with human adipose microvessels.