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This paper deals with the preview gust alleviation control system of an aircraft, which mitigates dangerous vertical acceleration due to wind gust using the forward wind velocity measured by the LIDAR (LIght Detection And Ranging). Although the vertical acceleration can be alleviated by preview control, the preview feedforward part tends to be sensitive to measurement errors. In order to maintain consistently high acceleration alleviation performance, the preview feedforward needs to be robust to errors. This paper presents a design method for preview feedforward gains that can reduce the effect of measurement errors. Nonlinear simulation results of a small jet aircraft are provided to show that the designed preview control gain can both alleviate vertical acceleration and be robust against random and bias errors.

Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1–5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2associated with the risk allele in these younger patients. DOCK2expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n= 61 individuals) identified cell-type-specific downregulation of DOCK2and a COVID-19-specific decreasing effect of the risk allele on DOCK2expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

Several industries require getting information of products as soon as possible during fermentation. However, the trade-off between sensing speed and data quantity presents challenges for forecasting fermentation product yields. In this study, we tried to develop AI models to forecast ethanol yields in yeast fermentation cultures, using cell morphological data. Our platform involves the quick acquisition of yeast morphological images using a nonstaining protocol, extraction of high-dimensional morphological data using image processing software, and forecasting of ethanol yields via supervised machine learning. We found that the neural network algorithm produced the best performance, which had a coefficient of determination of >0.9 even at 30 and 60 min in the future. The model was validated using test data collected using the CalMorph-PC(10) system, which enables rapid image acquisition within 10 min. AI-based forecasting of product yields based on cell morphology will facilitate the management and stable production of desired biocommodities.Graphical AbstractDiagram of AI-based forecasting of ethanol fermentation using yeast morphological data.

Herein, a calibration procedure to determine the depth positions of particles in a microfluidic channel via astigmatism particle tracking velocimetry (APTV) has been described. A neural network model focusing on the geometrical parameters of distorted particle images was developed to calibrate APTV. To demonstrate the efficiency of this procedure, the Poiseuille flow and depth of the particles, and dispersions in the microchannel were studied. The depth positions were determined with an uncertainty of ±1µm. The present results suggest that the particle position dispersion could be a result of the degree of particle image deformation and its deviation.

The successful prospective incorporation of in vitro transporter kinetics in physiologically based pharmacokinetic (PBPK) models to describe drug disposition remains challenging. Although determination of scaling factors to extrapolate in vitro to in vivo transporter kinetics has been facilitated by quantitative proteomics, no robust assessment comparing membrane recoveries between different cells/tissues has been made. HEK293 cells overexpressing OCT2, MATE1, and MATE2K or human kidney cortex were homogenized and centrifuged to obtain the total membrane fractions, which were subsequently subjected to liquid-liquid extraction followed by centrifugation and precipitation to isolate plasma membrane fractions. Plasma membrane recoveries determined by quantitation of the marker Na+/K+-ATPase in lysate and plasma membrane fractions were ≤20% but within 3-fold across different cells and tissues. A separate study demonstrated that recoveries are comparable between basolateral and apical membranes of renal proximal tubules, as measured by Na+/K+-ATPase and γ-glutamyl transpeptidase 1, respectively. The plasma membrane expression of OCT2, MATE1, and MATE2K was quantified and relative expression factors (REFs) were determined as the ratio between the tissue and cell concentrations. Corrections using plasma membrane recovery had minimal impact on REF values (<2-fold). In vitro transporter kinetics of metformin were extrapolated to in vivo using the corresponding REFs in a PBPK model. The simulated metformin exposures were within 2-fold of clinical exposure. These results demonstrate that transporter REFs based on plasma membrane expression enable a prediction of transporter-mediated drug disposition. Such REFs may be estimated without the correction of plasma membrane recovery when the same procedure is applied between different matrices.SIGNIFICANCE STATEMENTTransporter REFs based on plasma membrane expression enable in vitro-in vivo extrapolation of transporter kinetics. Plasma membrane recoveries as determined by the quantification of sodium-potassium adenosine triphosphatase were comparable between the in vitro and in vivo systems used in the present study, and therefore had minimal impact on the transporter REF values.

This paper presents a flight demonstration project for LIDAR-based gust alleviation control currently planned in Japan. The onboard coherent Doppler LIDAR has already been developed and validated by flight experiments. The wind velocity estimation algorithm has also been developed which can estimate two-dimensional distribution of wind field between two laser beams of the LIDAR system. These components are to be combined with the preview control law which utilizes the estimated wind velocities in front of the aircraft, and to be proven in the flight demonstration. This paper shows the results obtained so far and introduces the flight demonstration under planning.

ABSTRACTA 68-year-old woman under maintenance hemodialysis was admitted to our hospital with fever and dyspnea that had developed two days after the second vaccination with the 23-valent pneumococcal polysaccharide vaccine (PPV23). She had received the first vaccination with PPV23 five years earlier without any complications. Chest X-ray and computed tomography (CT) showed bilateral diffuse infiltrative and ground glass opacities. Bronchoalveolar lavage (BAL) revealed an abundance of eosinophils. A positive test result for PPV23 was obtained in the drug lymphocyte stimulation test. The patient was diagnosed as having eosinophilic pneumonia caused by the pneumococcal vaccination and was successfully treated by 3-week’s administration of a steroid. No disease recurrence was observed at the three-month follow-up. Thus, EP is a rare, but life-threating condition following pneumococcal vaccination.

P-glycoprotein (P-gp) is expressed at the blood-brain barrier (BBB) and restricts the penetration of its substrates into the central nervous system (CNS). In vitro substrate assessment for P-gp is frequently used to predict the in vivo relevance of P-gp-mediated efflux at the BBB. We have conducted a comprehensive review of literature focusing on the in vitro–in vivo correlation of P-gp efflux ratio (ER), and demonstrated that in vitro substrates of P-gp are also in vivo substrates at the BBB. It was of note that the in vitro ER in the MDCK-MDR1 cell line from National Institutes of Health was found to be a better predictor of in vivo ER than that from Netherlands Cancer Institute, with r2values of 0.813 and 0.531, respectively. Recently, a research group proposed that 98% of Biopharmaceutics Drug Disposition Classification System (BDDCS) class 1 drugs can penetrate the brain even when those compounds are shown as P-gp substrates in vitro. However, our data analysis suggested that in vitro ER can predict the in vivo brain penetration regardless of the class in BDDCS. Considering that very few marketed CNS drugs are in vivo substrates for P-gp, the in vitro substrate assessment of P-gp should be used in the early stages of drug discovery to select compounds that are most likely to penetrate the CNS to exert their pharmacologic action.

Organic anion transporting polypeptides (rodents, Oatps; human, OATPs) are primarily involved in the transmembrane transportation of a wide range of endogenous and exogenous compounds. Multiple mouse Oatp1isoforms are closely located on chromosome 6, where each isoform shows distinct tissue distribution; Oatp1b2, Oatp1a6, and Oatp1c1 are expressed exclusively in the liver, kidney, and cerebrum, respectively; Oatp1a1 in the liver and kidney; and Oatp1a4 in the liver and cerebrum. We have identified tissue-dependent differentially methylated region (T-DMR) around the transcriptional start site (TSS) of Oatp1b2, which correlates with its liver-specific expression. Bisulfite sequencing also demonstrated the presence of T-DMRs around the TSS in other Oatp1genes: CpG dinucleotides at +149 relative to the TSS for Oatp1c1; −48, +101, and +356 for Oatp1a4; −572 and −550 for Oatp1a1; and −122 and +216 for Oatp1a6were differentially methylated among the liver, kidney, and cerebrum. These methylation profiles were largely consistent with the tissue distribution of Oatp1 mRNAs. Chromatin immunoprecipitation assay revealed that the mRNA expression of Oatp1genes was accompanied by acetylated histone H3. Human OATP1B1and OATP1B3are located on chromosome 12p12 in the OATP1cluster; both show predominant expression in the liver. These genes also contained T-DMRs that were hypomethylated in the liver, compared with kidney cortex: −511, −411, and +92 relative to the TSS for OATP1B1and −331, +70, and +73 for OATP1B3. These results suggest that the difference in epigenetic profiles comprising DNA methylation and histone acetylation determines the distinct tissue distribution of Oatp/OATP mRNAs.

We have reported previously that the kidney- and liver-specific expression of transporters in mice involves the coordinated regulation by hepatocyte nuclear factor 1 (HNF1) and DNA methylation. The present study was aimed at investigating the role of this cascade in the transcriptional regulation of renal organic anion transporters (OATs) yet to be characterized in human and mouse. Luciferase assays and electrophoretic mobility-shift assays demonstrated that HNF1α/β enhances the promoter activity of OAT4/SLC22A11 via binding to the HNF1 motif located near the transcriptional start site (TSS). DNA methylation profiles of human OAT1, OAT3, OAT4, and urate transporter 1 (URAT1) were determined in human liver and kidney cortex by bisulfite sequencing. Most of the CpG dinucleotides around the TSSs of OAT1 and OAT3 were highly methylated in the liver compared with kidney cortex, being consistent with their tissue specificity, whereas the difference in the DNA methylation status was less remarkable between the two tissues for OAT4 and URAT1. Mouse Oat1 gene also contained CpG dinucleotides hypomethylated in the kidney and hypermethylated in the liver downstream its TSS, whereas two of the seven CpG dinucleotides around the TSS of mouse Oat3 were significantly methylated in the liver compared with the kidney. Taken together, these findings underscored the central role of HNF1α/β in the transcriptional regulation of OATs and highlighted DNA methylation-dependent gene silencing as one of the mechanisms underlying the tissue-specific transactivation by this master regulator.

The expression of drug transporters and metabolizing enzymes is a primary determinant of drug disposition. Chimeric mice with humanized liver, including PXB mice, are an available model that is permissive to the in vivo infection of hepatitis C virus (HCV), thus being a promising tool for investigational studies in development of new antiviral molecules. To investigate the potential of HCV infection to alter the pharmacokinetics of small molecule antiviral therapeutic agents in PXB mice, we have comprehensively determined the mRNA expression profiles of human ATP-binding cassette (ABC) transporters, solute carrier (SLC) transporters, and cytochrome P450 (P450) enzymes in the livers of these mice under noninfected and HCV-infected conditions. Infection of PXB mice with HCV resulted in an increase in the mRNA expression levels of a series of interferon-stimulated genes in the liver. For the majority of genes involved in drug disposition, minor differences in the mRNA expression of ABC and SLC transporters as well as P450s between the noninfected and HCV-infected groups were observed. The exceptions were statistically significantly higher expression of multidrug resistance-associated protein 4 and organic anion-transporting polypeptide 2B1 and lower expression of organic cation transporter 1 and CYP2D6 in HCV-infected mice. Furthermore, the enzymatic activities of the major human P450s were, in general, comparable in the two experimental groups. These data suggest that the pharmacokinetic properties of small molecule antiviral therapies in HCV-infected PXB mice are likely to be similar to those in noninfected PXB mice. However, caution is needed in the translation of this relationship to HCV-infected patients as the PXB mouse model does not accurately reflect the pathology of patients with chronic HCV infection.

Tissue-specific expression of transporters is tightly linked with their physiological functions through the regulation of the membrane transport of their substrates. We hypothesized that epigenetic regulation underlies the tissue-specific expression of mouse liver-specific transporters (Oatp1b2/Slco1b2, Ntcp/Slc10a1, Bsep/Abcb11, and Abcg5/g8). We examined their DNA methylation and histone modification profiles near the transcriptional start site (TSS) in the liver, kidney, and cerebrum. Genome-wide DNA methylation profiling with tissue-dependent differentially methylated region profiling with restriction tag-mediated amplification and subsequent bisulfite genomic sequencing demonstrated that the CpG dinucleotides around the TSS of Oatp1b2 (from -515 to +149 CpGs), Ntcp (from -481 to +495 CpGs), Bsep (from -339 to +282 CpGs), and Abcg5/g8 (from -161 to +5 CpGs for Abcg5, i.e., from -213 to -48 CpGs for Abcg8) were hypomethylated in the liver and hypermethylated in the kidney and cerebrum. The opposite pattern was observed for Pept2/Slc15a2 (from -638 to +4 CpGs), which was expressed in the kidney and cerebrum but not in the liver. These DNA methylation profiles are consistent with the tissue distribution of these transporters. A chromatin immunoprecipitation assay demonstrated that the histone H3 associated with Oatp1b2, Ntcp, Bsep, and Abcg5/g8 promoters was hyperacetylated in the liver but was acetylated very little in the kidney and cerebrum, whereas the upstream region of Pept2 was hyperacetylated only in the kidney and cerebrum. These results suggest the involvement of epigenetic systems in the tissue-specific expression of mouse transporters Oatp1b2, Ntcp, Bsep, Abcg5/g8, and Pept2.

Organic anion transporter 1 (OAT1/SLC22A6) is predominantly expressed in the proximal tubules of the kidney. Cumulative studies have shown its critical role in the tubular secretion of a variety of organic anions, including several clinically important drugs. In addition, OAT1 is also involved in the pharmacological effect of diuretics and the nephrotoxicity of antiviral drugs. In contrast to these functional characterizations, the regulatory mechanism of OAT1 expression is poorly understood. It was recently demonstrated that the expression of Oat1 was markedly reduced in the kidneys of hepatocyte nuclear factor 1alpha (Hnf1alpha)-null mice. However, in vitro evidence for the involvement of HNF1alpha and further analyses are required to illustrate the transcriptional regulation of OAT1 genes in more detail. Computational analysis of the potential transcription factor binding sites revealed that the HNF1-motif was conserved in the proximal-promoter region of human and mouse OAT1 genes. The mRNA expression of mouse organic anion transporter 1 was drastically reduced in Hnf1alpha-null mice compared with that in wild-type mice, which was consistent with a previous report (Maher et al., 2006). Forced expression of HNF1alpha alone or both HNF1alpha and HNF1beta enhanced the activity of human and mouse OAT1 promoters in the transactivation assays, whereas HNF1beta alone was not active. Mutations in the HNF1-motif significantly reduced this transactivation. Direct binding of HNF1alpha/HNF1alpha homodimer and HNF1alpha/HNF1beta heterodimer to the HNF1-motif found in the human OAT1 promoter was demonstrated by electrophoretic mobility shift assays. These results provide convincing evidence for the involvement of HNF1alpha/beta in the constitutive expression of human and mouse OAT1 in the kidney.

Expression of Urate transporter 1 (URAT1/SLC22A12) is restricted to the proximal tubules in the kidney, where it is responsible for the tubular reabsorption of urate. To elucidate the mechanism underlying its tissue-specific expression, the transcriptional regulation of the hURAT1 and mUrat1 genes was investigated. Hepatocyte nuclear factor 1 α (HNF1α) and HNF1β positively regulate minimal promoter activity of the URAT1 gene as shown by reporter gene assays. Electrophoretic mobility shift assays revealed binding of HNF1α and/or HNF1β to the HNF1 motif in the hURAT1 promoter. Furthermore, the mRNA expression of Urat1 is reduced in the kidneys of Hnf1α-null mice compared with wild-type mice, confirming the indispensable role of HNF1α in the constitutive expression of URAT1 genes. It was also shown that the proximal promoter region of mUrat1 was hypermethylated in the liver and kidney medulla, whereas this region was relatively hypomethylated in the kidney cortex. These methylation profiles are in a good agreement with the proximal tubule-restricted expression of mUrat1 in the kidney cortex. Taken together, these results strongly suggest that tissue-specific expression of the URAT1 genes is coordinately regulated by the transcriptional activation by HNF1α/HNF1β heterodimer and repression by DNA methylation.

Human organic anion transporter 3 (hOAT3/SLC22A8) is predominantly expressed in the proximal tubules of the kidney and plays a major role in the urinary excretion of a variety of organic anions. The promoter region of hOAT3 was characterized to elucidate the mechanism underlying the tissue-specific expression of hOAT3. The minimal promoter of hOAT3 was identified to be located approximately 300 base pairs upstream of the transcriptional start site, where there are canonical TATA and hepatocyte nuclear factor (HNF1) binding motifs, which are conserved in the rodent Oat3 genes. Transactivation assays revealed that HNF1alpha and HNF1beta markedly increased hOAT3 promoter activity, where the transactivation potency of HNF1beta was lower than that of HNF1alpha. Mutations in the HNF1 binding motif prevented the transactivation. Electrophoretic mobility shift assays demonstrated binding of the HNF1alpha/HNF1alpha homodimer or HNF1alpha/HNF1beta heterodimer to the hOAT3 promoter. It was also demonstrated that the promoter activity of hOAT3 is repressed by DNA methylation. Moreover, the expression of hOAT3 was activated de novo by forced expression of HNF1alpha alone or both HNF1alpha and HNF1beta together with the concomitant DNA demethylation in human embryonic kidney 293 cells that lack expression of endogenous HNF1alpha and HNF1beta, whereas forced expression of HNF1beta alone could not activate the expression of hOAT3. This suggests a synergistic action of the HNF1alpha/HNF1alpha homodimer or HNF1alpha/HNF1beta heterodimer and DNA demethylation for the constitutive expression of hOAT3. These results indicate that the tissue-specific expression of hOAT3 might be regulated by the concerted effect of genetic (HNF1alpha and HNF1beta) and epigenetic (DNA methylation) factors.

Classification of the biological activities of chemical substances is important for developing new medicines efficiently. Various machine learning methods are often employed to screen large libraries of compounds and predict the activities of new substances by training the molecular structure‐activity relationships. One such method is graph classification, in which a molecular structure can be represented in terms of a labeled graph with nodes that correspond to atoms and edges that correspond to the bonds between these atoms. In a conventional graph definition, atomic symbols and bond orders are employed as node and edge labels, respectively. In this study, we developed new graph definitions using the assignment of atom and bond types in the force fields of molecular dynamics methods as node and edge labels, respectively. We found that these graph definitions improved the accuracies of activity classifications for chemical substances using graph kernels with support vector machines and deep neural networks. The higher accuracies obtained using our proposed definitions can enhance the development of the materials informatics using graph‐based machine learning methods.