Perfluoropolyether-Based Gut-Liver-on-a-Chip for the Evaluation of First-Pass Metabolism and Oral Bioavailability of Drugs.

In the evolving field of drug discovery and development, multiorgans-on-a-chip and microphysiological systems are gaining popularity owing to their ability to emulate in vivo biological environments. Among the various gut-liver-on-a-chip systems for studying oral drug absorption, the chip developed in this study stands out with two distinct features: incorporation of perfluoropolyether (PFPE) to effectively mitigate drug sorption and a unique enterohepatic single-passage system, which simplifies the analysis of first-pass metabolism and oral bioavailability. By introducing a bolus drug injection into the liver compartment, hepatic extraction alone could be evaluated, further enhancing our estimation of intestinal availability. In a study on midazolam (MDZ), PFPE-based chips showed more than 20-times the appearance of intact MDZ in the liver compartment effluent compared to PDMS-based counterparts. Notably, saturation of hepatic metabolism at higher concentrations was confirmed by observations when the dose was reduced from 200 µM to 10 µM. This result was further emphasized when the metabolism was significantly inhibited by the coadministration of ketoconazole. Our chip, which is designed to minimize the dead volume between the gut and liver compartments, is adept at sensitively observing the saturation of metabolism and the effect of inhibitors. Using genome-edited CYP3A4/UGT1A1-expressing Caco-2 cells, the estimates for intestinal and hepatic availabilities were 0.96 and 0.82, respectively; these values are higher than the known human in vivo values. Although the metabolic activity in each compartment can be further improved, this gut-liver-on-a-chip can not only be used to evaluate oral bioavailability but also to carry out individual assessment of both intestinal and hepatic availability.

Application of machine learning techniques in population pharmacokinetics/pharmacodynamics modeling.

Population pharmacokinetics/pharmacodynamics (pop-PK/PD) consolidates pharmacokinetic and pharmacodynamic data from many subjects to understand inter- and intra-individual variability due to patient backgrounds, including disease state and genetics. The typical workflow in pop-PK/PD analysis involves the determination of the structure model, selection of the error model, analysis based on the base model, covariate modeling, and validation of the final model. Machine learning is gaining considerable attention in the medical and various fields because, in contrast to traditional modeling, which often assumes linear or predefined relationships, machine learning modeling learns directly from data and accommodates complex patterns. Machine learning has demonstrated excellent capabilities for prescreening covariates and developing predictive models. This review introduces various applications of machine learning techniques in pop-PK/PD research.

Programmed immobilization of living cells using independent click pairs.

Therapeutic devices incorporating living cells or tissues have been intensively investigated for applications in tissue engineering and regenerative medicine. Because many biological processes are governed by spatially dependent signals, programmable immobilization of materials is crucial for manipulating multiple types of cells. In this study, click chemistry substrates were introduced onto the surfaces of cells and cover glass, and the cells were fixed on the cover glass via covalent bonds for selective cell deposition. Azide group (Az)-labeled living cells were prepared by metabolic labeling with azido sugars. Following the introduction of Az, TCO (trans-cyclooctene) was metabolically labeled into the living cells by reacting with TCO-DBCO (dibenzocyclooctyne). Az and TCO in the cells were detected using DBCO-FAM (fluorescein)and tetrazine-Cy3, respectively. The mixture of Az-labeled green fluorescent protein HeLa cells and TCO-labeled red fluorescent protein HeLa cells was reacted in a culture dish in which three different cover glasses, DBCO-, tetrazine-, or methyl-coated, were added. Az- or TCO-labeled cells could be immobilized in a functional group-dependent manner. Next, tetrazine-labeled cells were incubated on TCO- or Az-labeled cell layers instead of cover glass. Functional group-dependent immobilization was also achieved in the cell layer. Introducing substrates for the click reaction could achieve cell-selective immobilization on different patterned glass surfaces, as well as cell-cell immobilization.

Relationship between Adsorption and Toxicity of Nephrotoxic Drugs in Microphysiological Systems (MPS).

Microphysiological systems (MPS) are an emerging technology for next-generation drug screening in non-clinical tests. Microphysiological systems are microfluidic devices that reconstitute the physiological functions of a human organ using a three-dimensional in vivo-mimicking microenvironment. In the future, MPSs are expected to reduce the number of animal experiments, improve prediction methods for drug efficacy in clinical settings, and reduce the costs of drug discovery. However, drug adsorption onto the polymers used in an MPS is a critical issue for assessment because it changes the concentration of the drug. Polydimethylsiloxane (PDMS), a basic material used for the fabrication of MPS, strongly adsorbs hydrophobic drugs. As a substitute for PDMS, cyclo-olefin polymer (COP) has emerged as an attractive material for low-adsorption MPS. However, it has difficulty bonding with different materials and, therefore, is not commonly used. In this study, we assessed the drug adsorption properties of each material constituting an MPS and subsequent changes in drug toxicity for the development of a low-adsorption MPSs using COP. The hydrophobic drug cyclosporine A showed an affinity for PDMS and induced lower cytotoxicity in PDMS-MPS but not in COP-MPS, whereas adhesive tapes used for bonding adsorbed a significant quantity of drugs, lowering their availability, and was cytotoxic. Therefore, easily-adsorbed hydrophobic drugs and bonding materials having lower cytotoxicity should be used with a low-adsorption polymer such as COP.

Blautia coccoides JCM1395T Achieved Intratumoral Growth with Minimal Inflammation: Evidence for Live Bacterial Therapeutic Potential by an Optimized Sample Preparation and Colony PCR Method.

We demonstrate that Blautia coccoides JCM1395T has the potential to be used for tumor-targeted live bacterial therapeutics. Prior to studying its in vivo biodistribution, a sample preparation method for reliable quantitative analysis of bacteria in biological tissues was required. Gram-positive bacteria have a thick outer layer of peptidoglycans, which hindered the extraction of 16S rRNA genes for colony PCR. We developed the following method to solve the issue; the method we developed is as follows. The homogenates of the isolated tissue were seeded on agar medium, and bacteria were isolated as colonies. Each colony was heat-treated, crushed with glass beads, and further treated with restriction enzymes to cleave DNAs for colony PCR. With this method, Blautia coccoides JCM1395T and Bacteroides vulgatus JCM5826T were individually detected from tumors in mice intravenously receiving their mixture. Since this method is very simple and reproducible, and does not involve any genetic modification, it can be applied to exploring a wide range of bacterial species. We especially demonstrate that Blautia coccoides JCM1395T efficiently proliferate in tumors when intravenously injected into tumor-bearing mice. Furthermore, these bacteria showed minimal innate immunological responses, i.e., elevated serum tumor necrosis factor α and interleukin-6, similar to Bifidobacterium sp., which was previously studied as a therapeutic agent with a small immunostimulating effect.

Application of machine learning techniques to the analysis and prediction of drug pharmacokinetics.

In this review, we describe the current status and challenges in applying machine-learning techniques to the analysis and prediction of pharmacokinetic data. The theory of pharmacokinetics has been developed over decades on the basis of physiology and reaction kinetics. Mathematical models allow the reduction of pharmacokinetic data to parameter values, giving insight and understanding into ADME processes and predicting the outcome of different dosing scenarios. However, much information hidden in the data is lost through conceptual simplification with models. It is difficult to use mechanistic models alone to predict diverse pharmacokinetic time profiles, including inter-drug and inter-individual differences, in a cross-sectional manner. Machine learning is a prediction platform that can handle complex phenomena through data-driven analysis. As a resule, machine learning has been successfully adopted in various fields, including image recognition and language processing, and has been used for over two decades in pharmacokinetic research, primarily in the area of quantitative structure-activity relationships for pharmacokinetic parameters. Machine-learning models are generally known to provide better predictive performance than conventional linear models. Owing to the recent success in deep learning, models with new structures are being consistently proposed. These models include transfer learning and generative adversarial networks, which contribute to the effective use of a limited amount of data by diverting existing similar models or generating pseudo-data. How to make such newly emerging machine learning technologies applicable to meet challenges in the pharmacokinetics/pharmacodynamics field is now the key issue.

Application of perfluoropolyether elastomers in microfluidic drug metabolism assays.

Recently, increasing attention has been paid to liver-on-a-chip models for both pharmacokinetics and toxicity (ADMET) screenings. Although polydimethylsiloxane (PDMS) is the most popular material for the fabrication of microfluidic devices, its extensive sorption of hydrophobic drugs limits its applications. Therefore, we investigated a chemically repellent material, perfluoropolyether (PFPE) elastomer, as an alternative to PDMS. Primary rat hepatocytes cultured in the PFPE microfluidic device were polygonal or cuboidal in shape and had one or two prominent nuclei, as when cultured in 96-well plates. When hepatocytes were cultured in the PFPE microfluidic device and exposed to dynamic flow, the production of albumin and urea increased 3.94- and 1.72-fold, respectively, compared with no dynamic flow. Exposure to dynamic flow did not result in obvious changes in the expression of cytochrome P450, but increased the metabolic activity of hepatocytes compared to under static conditions. PFPE devices did not absorb midazolam, which was extensively absorbed by PDMS devices. However, the sorption of bufuralol could not be avoided even with PFPE devices. Solvent swelling experiments highlighted much better chemical repellency with PFPE than with PDMS. Hansen solubility parameters and sphere radius were estimated from the solvent swelling experiments. The relative energy distance (RED) of bufuralol to PFPE was much smaller than that of other three drugs tested, reasonably explaining the high sorption of bufuralol to PFPE. Although sorption into PFPE cannot be completely avoided, PFPE microfluidic devices may provide a better performance in ADMET evaluation than PDMS.

Disposition of E-selectin-targeting liposomes in tumor spheroids with a perfusable vascular network.

We constructed tumor spheroids with a perfusable vascular network to assess drug delivery systems that target the tumor vasculature. A tricultured tumor spheroid containing human umbilical vein endothelial cells (HUVECs) was placed in the central compartment of a microfluidic device, and the HUVECs were seeded into the microslit channels on both sides. Angiogenic sprouts began to form within a few days, from both the tumor spheroids and microchannels, and became more abundant and branched, while attracting each other, over time. A continuous vascular network of HUVECs was fully formed on Day 7. The uptake of 3'-(1-carboxy)ethyl sialyl Lewis X mimic (3'-CE sLeX mimic) liposomes, which have previously been proven to recognize E-selectin, in vascular-perfusable tumor spheroids was assessed. 3'-CE sLeX mimic and pegylated liposomes were rarely taken up, but when the vascular network was pretreated with TNF-α and IL-1ß, 3'-CE sLeX mimic liposomes accumulated considerably more in endothelial cells and their vicinity. Taken together, along with the known in vivo expression of E-selectin in tumor angiogenic blood vessels, these results suggest that 3'-CE sLeX mimic liposomes are a promising carrier for targeting tumor vasculature. Furthermore, proinflammatory cytokine treatment may be appropriate for use with vascular-perfusable tumor spheroids in pharmacokinetic studies.

Intestinal Permeability of Drugs in Caco-2 Cells Cultured in Microfluidic Devices.

Microfluidic devices are attracting attention for their ability to provide a biomimetic microenvironment wherein cells are arranged in a particular pattern and provided fluidic and mechanical forces. In this study, we evaluated drug transport across Caco-2 cell layers in microfluidic devices and investigated the effects of fluid flow on drug transport and metabolism. We designed a microfluidic device that comprises two blocks of polydimethylsiloxane and a sandwiched polyethylene terephthalate membrane with pores 3.0 µm in diameter. When cultured in a dynamic fluid environment, Caco-2 cells were multilayered and developed microvilli on the surface as compared with a static environment. Drugs with higher lipophilicity exhibited higher permeability across the Caco-2 layers, as well as in the conventional method using Transwells, and the fluidic conditions had little effect on permeability. In the Caco-2 cell layers cultured in Transwells and microfluidic devices, the basal-to-apical transport of rhodamine 123, a substrate of P-glycoprotein, was greater than the apical-to-basal transport, and the presence of tariquidar, an inhibitor of P-glycoprotein, completely diminished asymmetric transport. Furthermore, fluidic conditions promoted the metabolism of temocapril by carboxylesterases. On the other hand, we showed that fluidic conditions have little effect on gene expression of several transporters and metabolic enzymes. These results provide useful information regarding the application of microfluidic devices in drug transport and metabolism studies.

CREB is a potential marker associated with drug-induced liver injury: Identification and validation through transcriptome database analysis.

Drug-induced liver injury (DILI) is the main cause of failure in drug development and postapproval withdrawal. Although toxicogenomic techniques provide an unprecedented opportunity for mechanistic assessment and biomarker discovery, they are not suitable for the screening of large numbers of exploratory compounds in early drug discovery. Using a comprehensive analysis of toxicogenomics (TGx) data, we aimed to find DILI-relevant transcription factors (TFs) that could be incorporated into a reporter gene assay system. Gene set enrichment analysis (GSEA) of the Open TG-GATEs dataset highlighted 4 DILI-relevant TFs, including CREB, NRF2, ELK-1, and E2F. Using ten drugs with already assigned idiosyncratic toxicity (IDT) risks, reporter gene assays were conducted in HepG2 cells in the presence of the S9 mix. There were weak correlations between NRF2 activity and IDT risk, whereas strong correlations were observed between CREB activity and IDT risk. In addition, CREB activation associated with 3 Withdrawn/Black box Warning drugs was reversed by pretreatment with a PKA inhibitor. Collectively, we suggest that CREB might be a sensitive biomarker for DILI prediction, and its response to stress induced by high-risk drugs might be primarily regulated by the PKA/CREB signaling pathway.

Cytosolic Ca2+-dependent Ca2+ release activity primarily determines the ER Ca2+ level in cells expressing the CPVT-linked mutant RYR2.

Type 2 ryanodine receptor (RYR2) is a cardiac Ca2+ release channel in the ER. Mutations in RYR2 are linked to catecholaminergic polymorphic ventricular tachycardia (CPVT). CPVT is associated with enhanced spontaneous Ca2+ release, which tends to occur when [Ca2+]ER reaches a threshold. Mutations lower the threshold [Ca2+]ER by increasing luminal Ca2+ sensitivity or enhancing cytosolic [Ca2+] ([Ca2+]cyt)-dependent activity. Here, to establish the mechanism relating the change in [Ca2+]cyt-dependent activity of RYR2 and the threshold [Ca2+]ER, we carried out cell-based experiments and in silico simulations. We expressed WT and CPVT-linked mutant RYR2s in HEK293 cells and measured [Ca2+]cyt and [Ca2+]ER using fluorescent Ca2+ indicators. CPVT RYR2 cells showed higher oscillation frequency and lower threshold [Ca2+]ER than WT cells. The [Ca2+]cyt-dependent activity at resting [Ca2+]cyt, Arest, was greater in CPVT mutants than in WT, and we found an inverse correlation between threshold [Ca2+]ER and Arest. In addition, lowering RYR2 expression increased the threshold [Ca2+]ER and a product of Arest, and the relative expression level for each mutant correlated with threshold [Ca2+]ER, suggesting that the threshold [Ca2+]ER depends on the net Ca2+ release rate via RYR2. Modeling reproduced Ca2+ oscillations with [Ca2+]cyt and [Ca2+]ER changes in WT and CPVT cells. Interestingly, the [Ca2+]cyt-dependent activity of specific mutations correlated with the age of disease onset in patients carrying them. Our data suggest that the reduction in threshold [Ca2+]ER for spontaneous Ca2+ release by CPVT mutation is explained by enhanced [Ca2+]cyt-dependent activity without requiring modulation of the [Ca2+]ER sensitivity of RYR2.

Generation of Tetrafluoroethylene-Propylene Elastomer-Based Microfluidic Devices for Drug Toxicity and Metabolism Studies.

Polydimethylsiloxane (PDMS) is widely used to fabricate microfluidic organs-on-chips. Using these devices (PDMS-based devices), the mechanical microenvironment of living tissues, such as pulmonary respiration and intestinal peristalsis, can be reproduced in vitro. However, the use of PDMS-based devices in drug discovery research is limited because of their extensive absorption of drugs. In this study, we investigated the feasibility of the tetrafluoroethylene-propylene (FEPM) elastomer to fabricate a hepatocyte-on-a-chip (FEPM-based hepatocyte chip) with lower drug absorption. The FEPM-based hepatocyte chip expressed drug-metabolizing enzymes, drug-conjugating enzymes, and drug transporters. Also, it could produce human albumin. Although the metabolites of midazolam and bufuralol were hardly detected in the PDMS-based hepatocyte chip, they were detected abundantly in the FEPM-based hepatocyte chip. Finally, coumarin-induced hepatocyte cytotoxicity was less severe in the PDMS-based hepatocyte chip than in the FEPM-based hepatocyte chip, reflecting the different drug absorptions of the two chips. In conclusion, the FEPM-based hepatocyte chip could be a useful tool in drug discovery research, including drug metabolism and toxicity studies.

Prediction of HIV drug resistance based on the 3D protein structure: Proposal of molecular field mapping.

A method for predicting HIV drug resistance by using genotypes would greatly assist in selecting appropriate combinations of antiviral drugs. Models reported previously have had two major problems: lack of information on the 3D protein structure and processing of incomplete sequencing data in the modeling procedure. We propose obtaining the 3D structural information of viral proteins by using homology modeling and molecular field mapping, instead of just their primary amino acid sequences. The molecular field potential parameters reflect the physicochemical characteristics associated with the 3D structure of the proteins. We also introduce the Bayesian conditional mutual information theory to estimate the probabilities of occurrence of all possible protein candidates from an incomplete sequencing sample. This approach allows for the effective use of uncertain information for the modeling process. We applied these data analysis techniques to the HIV-1 protease inhibitor dataset and developed drug resistance prediction models with reasonable performance.

Usability of Polydimethylsiloxane-Based Microfluidic Devices in Pharmaceutical Research Using Human Hepatocytes.

A liver-on-a-chip (liver-chip) is a microfluidic device carrying liver cells such as human hepatocytes. It is used to reproduce a part of liver function. Many microfluidic devices are composed of polydimethylsiloxane (PDMS), which is a type of silicone elastomer. PDMS is easy to process and suitable for cell observation, but its high hydrophobicity carries the risk of drug absorption. In this study, we evaluated drug absorption to the PDMS device and investigated the drug responsiveness of human hepatocytes cultured in the PDMS device (hepatocyte-chips). First, the absorption rates of 12 compounds to the PDMS device were measured. The absorption rates of midazolam, bufuralol, cyclosporine A, and verapamil were 92.9, 71.7, 71.4, and 99.6%, respectively, but the other compounds were poorly absorbed. Importantly, the absorption rate of the compounds was correlated with their octanol/water distribution coefficient (log D) values (R2 = 0.76). Next, hepatocyte-chips were used to examine the response to drugs, which are typically used to evaluate hepatic functions. Using the hepatocyte-chips, we could confirm the responsiveness of drugs including cytochrome P450 (CYP) inducers and farnesoid X receptor (FXR) ligands. We believe that our findings will contribute to drug discovery research using PDMS-based liver-chips.

Dynamic changes in gene-to-gene regulatory networks in response to SARS-CoV-2 infection.

The current pandemic of SARS-CoV-2 has caused extensive damage to society. The characterization of SARS-CoV-2 profiles has been addressed by researchers globally with the aim of resolving this disruptive crisis. This investigation process is indispensable to understand how SARS-CoV-2 behaves in human host cells. However, little is known about the systematic molecular mechanisms involved in the effects of SARS-CoV-2 infection on human host cells. Here, we present gene-to-gene regulatory networks in response to SARS-CoV-2 using a Bayesian network. We examined the dynamic changes in the SARS-CoV-2-purturbated networks established by our proposed framework for gene network analysis, thus revealing that interferon signaling gradually switched to the subsequent inflammatory cytokine signaling cascades. Furthermore, we succeeded in capturing a COVID-19 patient-specific network in which transduction of these signals was concurrently induced. This enabled us to explore the local regulatory systems influenced by SARS-CoV-2 in host cells more precisely at an individual level. Our panel of network analyses has provided new insights into SARS-CoV-2 research from the perspective of cellular systems.

Minocycline Hydrochloride Controlled-release Microsphere Preparation Process Optimization Based on the Robust Design Method.

OBJECTIVES: The objective of the present study is to establish a robust preparation method that could steadily produce minocycline hydrochloride (MCH) microspheres regardless of used polymer types. MATERIALS AND METHODS: Taguchi's Robust Experimental Design methodology was employed to optimize the process parameters for MCH-loaded poly(D,L-lactide-co-glycolide) (PLGA) microspheres. In the experimental design, seven controllable factors, i.e., preparation method, pH of the aqueous phase, volume of the aqueous phase, volume of dichloromethane, rotation speed, temperature, and amount of polyvinyl alcohol, were considered for the optimization of process parameters. PLGA types with different lactide/glycolide ratios were considered the uncontrollable (noise) factor. Based on the L18 orthogonal array, 18 experimental runs were conducted for each type of PLGA. The encapsulation efficiency (EE) and in vitro release rate were evaluated for all the prepared formulations. RESULTS: Regardless of the PLGA type with different lactic/glycolic acid ratios, microspheres prepared via the solid-in-oil-in-water (S/O/W) method, showed a much higher EE and faster drug release than the microspheres prepared via the co-solvent method. Preparation methods, pH of the aqueous phase, and volume of the aqueous phase were the most influencing parameters on the EE. The confirmation experiment results indicated that the signal-to-noise ratio increased by 5.76 db from that of an initial condition. The release of minocycline was fastest with the PLGA (50:50) microspheres, followed by PLGA (75:25) and PLGA (85:15). CONCLUSION: Although the interaction between the selected factors in the evaluation was ignored, the orthogonal array design of the experiment based on Taguchi's robust experimental design methodology was sufficient to optimize the process parameters for the PLGA microspheres of MCH. The S/O/W was the main factor affecting the EE. Microspheres prepared via the S/O/W method exhibited a higher EE and faster drug release than the microspheres prepared via co-solvent method. The pH and volume of the aqueous phase were also effective parameters on the EE. A robust experimental design has been successfully applied to the optimization of the process parameters for microsphere preparation.

Biosorption-based 64Cu-labeling of bacteria for pharmacokinetic positron-emission tomography.

Biosorption-based bacterial 64Cu-labeling and its application in pharmacokinetic positron-emission tomography (PET) were investigated. Both gram-positive and gram-negative bacteria were efficiently labeled with [64Cu]Cu2+ ion in saline at room temperature within 5 min. The labeling ratio for Escherichia coli drastically decreased with trypsin pretreatment and the co-presence of excess Cu2+ ion, indicating the existence of specific Cu2+ binding sites on the E. coli cell surface. Washing with lysogeny broth medium was effective in purifying 64Cu-labeled E. coli for kinetic study; the labeling stability was approximately 90% in serum for 15 min. According to dynamic PET imaging in colon-26 tumor-bearing mice, 64Cu-labeled E. coli immediately disappeared from the blood circulation and primarily accumulated in the liver. In addition, transient pulmonary distribution was observed, being in a dose-dependently accelerated manner. Considering the simplicity and versatility of biosorption-based bacterial 64Cu-labeling without genetic modification, the early-phase pharmacokinetic PET with 64Cu-labeled bacteria is promising for assessing toxicological aspects of bacteria-mediated cancer therapy as well as a variety of bacterial pathogenicities in infectious diseases.

The Application of the in-Situ Hyperthermia Emission from Acoustic Nanodroplets for Theranostic Dual-Imaging and Antitumor Modalities.

In this study, we have developed a theranostic nanocarrier that can emit heat upon the exposure to ultrasound (US) irradiation as well as the generation of a contrast signal that can be detected with ultrasonography. The prepared acoustic nanodroplets (NDs) made with liquid perfluporopentane (PFPn) had an average size of 197.7 ± 3.6 nm in diameter and were stable in vitro for 60 min. US irradiation at 2 W.cm-2 induced phase change of NDs into bubbles in vitro. On the other hand, the intra-tumor injection of NDs in combination with US irradiation induced thermal emission in situ in B16BL6 melanoma tumor implanted into mice and the emission areas have mostly covered the tumor site. Also, the combination between NDs and US irradiation has inhibited the tumor growth. Under this condition, the heat shock protein (HSP70) in tumor was significantly upregulated after 6 h of the treatment of NDs with US. Thus, we have developed a therapeutic system with multiple theranostic modalities composed of acoustic NDs and US irradiation applicable to the tumor treatment on the external surface of the body.

System-Based Differential Gene Network Analysis for Characterizing a Sample-Specific Subnetwork.

Gene network estimation is a method key to understanding a fundamental cellular system from high throughput omics data. However, the existing gene network analysis relies on having a sufficient number of samples and is required to handle a huge number of nodes and estimated edges, which remain difficult to interpret, especially in discovering the clinically relevant portions of the network. Here, we propose a novel method to extract a biomedically significant subnetwork using a Bayesian network, a type of unsupervised machine learning method that can be used as an explainable and interpretable artificial intelligence algorithm. Our method quantifies sample specific networks using our proposed Edge Contribution value (ECv) based on the estimated system, which realizes condition-specific subnetwork extraction using a limited number of samples. We applied this method to the Epithelial-Mesenchymal Transition (EMT) data set that is related to the process of metastasis and thus prognosis in cancer biology. We established our method-driven EMT network representing putative gene interactions. Furthermore, we found that the sample-specific ECv patterns of this EMT network can characterize the survival of lung cancer patients. These results show that our method unveils the explainable network differences in biological and clinical features through artificial intelligence technology.

Effects of Tissue Pressure on Transgene Expression Characteristics via Renal Local Administration Routes from Ureter or Renal Artery in the Rat Kidney.

We previously developed a renal pressure-mediated transfection method (renal pressure method) as a kidney-specific in vivo gene delivery system. However, additional information on selecting other injection routes and applicable animals remains unclear. In this study, we selected renal arterial and ureteral injections as local administration routes and evaluated the characteristics of gene delivery such as efficacy, safety, and distribution in pressured kidney of rat. Immediately after the naked pDNA injection, via renal artery or ureter, the left kidney of the rat was pressured using a pressure controlling device. Transfection efficiency of the pressured kidney was about 100-fold higher than that of the injection only group in both administration routes. The optimal pressure intensity in the rat kidney was 1.2 N/cm2 for renal arterial injection and 0.9 N/cm2 for ureteral injection. We found that transgene expression site differs according to administration route: cortical fibroblasts and renal tubule in renal arterial injection and cortical and medullary tubule and medullary collecting duct in ureteral injection. This is the first report to demonstrate that the renal pressure method can also be effective, after renal arterial and ureteral injections, in rat kidney.