Gene count normalization in single-cell imaging-based spatially resolved transcriptomics

Recent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations in fixed tissues. Normalization of gene expression data is often needed to account for technical factors that may confound underlying biological signals. Here, we investigate the potential impact of different gene count normalization methods with different targeted gene panels in the analysis and interpretation of im-SRT data. Using different simulated gene panels that overrepresent genes expressed in specific tissue regions or cell types, we demonstrate how normalization methods based on detected gene counts per cell differentially impact normalized gene expression magnitudes in a region- or cell type-specific manner. We show that these normalization-induced effects may reduce the reliability of downstream analyses including differential gene expression, gene fold change, and spatially variable gene analysis, introducing false positive and false negative results when compared to results obtained from gene panels that are more representative of the gene expression of the tissue's component cell types. These effects are not observed with normalization approaches that do not use detected gene counts for gene expression magnitude adjustment, such as with cell volume or cell area normalization. We recommend using non-gene count-based normalization approaches when feasible and evaluating gene panel representativeness before using gene count-based normalization methods if necessary. Overall, we caution that the choice of normalization method and gene panel may impact the biological interpretation of the im-SRT data.

In Vitro-In Vivo Extrapolation and Scaling Factors for Clearance of Human and Preclinical Species with Liver Microsomes and Hepatocytes

In vitro-in vivo extrapolation ((IVIVE) and empirical scaling factors (SF) of human intrinsic clearance (CL_int) were developed using one of the largest dataset of 455 compounds with data from human liver microsomes (HLM) and human hepatocytes (HHEP). For extended clearance classification system (ECCS) class 2/4 compounds, linear SFs (SF_lin) are approximately 1, suggesting enzyme activities in HLM and HHEP are similar to those in vivo under physiological conditions. For ECCS class 1A/1B compounds, a unified set of SFs was developed for CL_int. These SFs contain both SF_lin and an exponential SF (SF_β) of fraction unbound in plasma (f_u,p). The unified SFs for class 1A/1B eliminate the need to identify the transporters involved prior to clearance prediction. The underlying mechanisms of these SFs are not entirely clear at this point, but they serve practical purposes to reduce biases and increase prediction accuracy. Similar SFs have also been developed for preclinical species. For HLM-HHEP disconnect (HLM > HHEP) ECCS class 2/4 compounds that are mainly metabolized by cytochrome P450s/FMO, HLM significantly overpredicted in vivo CL_int, while HHEP slightly underpredicted and geometric mean of HLM and HHEP slightly overpredicted in vivo CL_int. This observation is different than in rats, where rat liver microsomal CL_int correlates well with in vivo CL_int for compounds demonstrating permeability-limited metabolism. The good CL_int IVIVE developed using HLM and HHEP helps build confidence for prospective predictions of human clearance and supports the continued utilization of these assays to guide structure-activity relationships to improve metabolic stability.

A mutation operator self-adaptive differential evolution particle swarm optimization algorithm for USV navigation

To keep the global search capability and robustness for unmanned surface vessel (USV) path planning, an improved differential evolution particle swarm optimization algorithm (DePSO) is proposed in this paper. In the optimization process, approach to optimal value in particle swarm optimization algorithm (PSO) and mutation, hybridization, selection operation in differential evolution algorithm (DE) are combined, and the mutation factor is self-adjusted. First, the particle population is initialized and the optimization objective is determined, the individual and global optimal values are updated. Then differential variation is conducted to produces new variables and cross over with the current individual, the scaling factor is adjusted adaptively with the number of iterations in the mutation process, particle population is updated according to the hybridization results. Finally, the convergence of the algorithm is determined according to the decision standard. Numerical simulation results show that, compared with conventional PSO and DE, the proposed algorithm can effectively reduce the path intersection points, and thus greatly shorten the overall path length.

A Low-Latency RDP-CORDIC Algorithm for Real-Time Signal Processing of Edge Computing Devices in Smart Grid Cyber-Physical Systems

Smart grids are being expanded in scale with the increasing complexity of the equipment. Edge computing is gradually replacing conventional cloud computing due to its low latency, low power consumption, and high reliability. The CORDIC algorithm has the characteristics of high-speed real-time processing and is very suitable for hardware accelerators in edge computing devices. The iterative calculation method of the CORDIC algorithm yet leads to problems such as complex structure and high consumption of hardware resource. In this paper, we propose an RDP-CORDIC algorithm which pre-computes all micro-rotation directions and transforms the conventional single-stage iterative structure into a three-stage and multi-stage combined iterative structure, thereby enabling it to solve the problems of the conventional CORDIC algorithm with many iterations and high consumption. An accuracy compensation algorithm for the direction prediction constant is also proposed to solve the problem of high ROM consumption in the high precision implementation of the RDP-CORDIC algorithm. The experimental results showed that the RDP-CORDIC algorithm had faster computation speed and lower resource consumption with higher guaranteed accuracy than other CORDIC algorithms. Therefore, the RDP-CORDIC algorithm proposed in this paper may effectively increase computation performance while reducing the power and resource consumption of edge computing devices in smart grid systems.

Sensitivity Enhanced Ecofriendly UV Spectrophotometric Methods for Quality Control of Telmisartan and Benidipine Formulations: Comparison of Whiteness and Greenness with HPLC Methods

The development of an environmentally friendly analytical technique for simultaneous measurement of medicines with large concentration differences is difficult yet critical for environmental protection. Hence, in this work, new manipulated UV-spectroscopic methods with high scaling factors were established for concurrent quantification of telmisartan (TEL) and benidipine (BEN) in fixed-dose combinations. Two different methods were developed and established by calculation of peak height at zero crossing point of second derivative and the ratio of first derivative spectra with a scaling factor of 200 and 100, respectively. The absorption difference between the peaks and troughs of the ratio spectra, as well as continuous subtraction from ratio spectra, were established as additional methods. In addition, new procedures were validated using ICH recommendations. The proposed methods’ linearity curves were constructed in the range of 0.5–10 µg mL⁻¹ and 1–30 µg mL⁻¹ for BEN and TEL, respectively, under optimized conditions. Furthermore, both the detection (0.088–0.139 µg mL⁻¹ for BEN and 0.256–0.288 µg mL⁻¹ for TEL) and quantification limits (0.293–0.465 µg mL⁻¹ for BEN and 0.801–0.962 µg mL⁻¹ for TEL) were adequate for quantifying both analytes in the formulation ratios. The accuracy and precision were confirmed by the good recovery percent (98.37%–100.6%), with low percent relative error (0.67%–1.70%) and less than 2 percent relative standard deviation, respectively. The specificity of the methods was proven by accurate and precise outcomes from the standard addition method and analysis of laboratory mixed solutions with large differences in concentrations of both analytes. Finally, the BEN and TEL content of the formulations was determined simultaneously without prior separation using these first ever reported spectroscopic methods. Furthermore, developed UV derivative spectroscopic methods demonstrated high greenness and whiteness when compared to the reported HPLC methods. These findings show that the projected methods were effective, practical, and environmentally acceptable for quality control of BEN and TEL in multicomponent formulations.

Pin-on-Disc Modelling with Mesh Deformation Using Discrete Element Method

The pin-on-disc test is a standard sliding wear test used to analyse sliding properties, including wear contour and wear volume. In this study, long-term laboratory test performance is compared with a short-term numerical model. A discrete element method (DEM) approach combined with an Archard wear model and a deformable geometry technique is used. The effect of mesh size on wear results is evaluated, and a scaling factor is defined to relate the number of revolutions between the experiment and the numerical model. The simulation results indicate that the mesh size of the disc has a significant effect on the wear contour. The wear depth and wear width follow a normal distribution after experiencing a run-in phase, while the wear volume has a quadratic relation with the number of revolutions. For the studied material combination, the calibration of the wear coefficient shows that the wear volume of the pin-on-disc test accurately matches the simulation results for a minimum of eight revolutions with a wear coefficient lower than 2 × 10^-11 Pa^-1.

Oscillations make a self-scaled model for honeybees' visual odometer reliable regardless of flight trajectory

Honeybees foraging and recruiting nest-mates by performing the waggle dance need to be able to gauge the flight distance to the food source regardless of the wind and terrain conditions. Previous authors have hypothesized that the foragers’ visual odometer mathematically integrates the angular velocity of the ground image sweeping backward across their ventral viewfield, known as translational optic flow. The question arises as to how mathematical integration of optic flow (usually expressed in radians/s) can reliably encode distances, regardless of the height and speed of flight. The vertical self-oscillatory movements observed in honeybees trigger expansions and contractions of the optic flow vector field, yielding an additional visual cue called optic flow divergence. We have developed a self-scaled model for the visual odometer in which the translational optic flow is scaled by the visually estimated current clearance from the ground. In simulation, this model, which we have called SOFIa, was found to be reliable in a large range of flight trajectories, terrains and wind conditions. It reduced the statistical dispersion of the estimated flight distances approximately 10-fold in comparison with the mathematically integrated raw optic flow model. The SOFIa model can be directly implemented in robotic applications based on minimalistic visual equipment.

In vitro-in vivo extrapolation of metabolic clearance using human liver microsomes: factors showing variability and their normalization

In vitro-in vivo extrapolation (IVIVE) using human liver microsomes has been widely used to predict metabolic clearance, but some of the factors used in the process of prediction show variability for the same compound: notably, microsomal intrinsic clearance values corrected by the unbound fraction (CL_{int, u}), physiological parameters used for scale-up, and the source of in vivo clearance data.The purpose of this study was to assess the correlation between in vitro and in vivo CL_int with a focus on factors showing variability using four cytochrome P450 (CYP)3A substrates.We surveyed in vivo clearance values in literature and also determined the microsomal CL_{int, u} values. A scaling factor (SF_direct) was defined as in vivo CL_int divided by the microsomal CL_{int, u}, which ranged from 1190 to 2310 (mg protein per kg body weight). The application of a mean SF_direct of 1600 (mg protein per kg body weight) and further normalization by the microsomal CL_{int, u} values of midazolam, the most commonly used substrate, resulted in improved prediction accuracy for CL_{int, u} values from various microsomal batches.The results suggest the normalization of variability might be useful for predicting the in vivo CL_int.

Impact of Intracellular Concentrations on Metabolic Drug-Drug Interaction Studies

Accurate prediction of drug-drug interactions (DDI) is a challenging task in drug discovery and development. It requires determination of enzyme inhibition in vitro which is highly system-dependent for many compounds. The aim of this study was to investigate whether the determination of intracellular unbound concentrations in primary human hepatocytes can be used to bridge discrepancies between results obtained using human liver microsomes and hepatocytes. Specifically, we investigated if Kp_uu could reconcile differences in CYP enzyme inhibition values (K_i or IC₅₀). Firstly, our methodology for determination of Kp_uu was optimized for human hepatocytes, using four well-studied reference compounds. Secondly, the methodology was applied to a series of structurally related CYP2C9 inhibitors from a Roche discovery project. Lastly, the Kp_uu values of three commonly used CYP3A4 inhibitors—ketoconazole, itraconazole, and posaconazole—were determined and compared to compound-specific hepatic enrichment factors obtained from physiologically based modeling of clinical DDI studies with these three compounds. Kp_uu obtained in suspended human hepatocytes gave good predictions of system-dependent differences in vitro. The Kp_uu was also in fair agreement with the compound-specific hepatic enrichment factors in DDI models and can therefore be used to improve estimations of enrichment factors in physiologically based pharmacokinetic modeling.

Assessment of Transporter-Mediated and Passive Hepatic Uptake Clearance Using Rifamycin-SV as a Pan-Inhibitor of Active Uptake

The use of in vitro data for the quantitative prediction of transporter-mediated clearance is critical. Central to this evaluation is the use of hepatocytes, since they contain the full complement of transporters and metabolic enzymes. In general, uptake clearance (CL_uptake) is evaluated by measuring the appearance of compound in the cell. Passive clearance (CL_pd) is often determined by conducting parallel studies at 4 °C or by attempting to saturate uptake pathways. Both approaches have their limitations. Recent studies have proposed the use of Rifamycin-SV (RFV) as a pan-inhibitor of hepatic uptake pathways. In our studies, we confirm that transport activity of all major hepatic uptake transporters is inhibited significantly by RFV at 1 mM (OATP1B1, 1B3, and 2B1 = NTCP (80%), OCT1 (65%), OAT2 (60%)). Under these incubation conditions, we found that the free intracellular concentration of RFV is ∼175 μM and that several major CYPs and UGTs can be reversibly inhibited. Using this approach, we also determined CL_uptake and CL_pd of nine known OATP substrates across three different lots of human hepatocytes. The scaling factors generated for these compounds at 37 °C with RFV and 4 °C were found to be similar. The CL_pd of passively permeable compounds like metoprolol and semagacestat were found to be higher at 37 °C compared to 4 °C, indicating a temperature effect on these compounds. In addition, our data also suggests that incorporation of medium concentrations into CL_uptake and CL_pd calculations may be critical for highly protein bound and highly lipophilic drugs. Overall, our data indicate that RFV, instead of 4 °C, can be reliably used to measure CL_uptake and CL_pd of drugs.

Hepatocyte nuclear factor 4α is required for cell differentiation and homeostasis in the adult mouse gastric epithelium

We have previously shown that the sequential transcription factors Xbp1→Mist1 (Bhlha15) govern the ultrastructural maturation of the secretory apparatus in enzyme-secreting zymogenic chief cells (ZCs) in the gastric unit. Here we sought to identify transcriptional regulators upstream of X-box binding protein 1 (XBP1) and MIST1. We used immunohistochemistry to characterize Hnf4α(flox/flox) adult mouse stomachs after tamoxifen-induced deletion of Hnf4α We used qRT-PCR, Western blotting, and chromatin immunoprecipitation to define the molecular interaction between hepatocyte nuclear factor 4 alpha (HNF4α) and Xbp1 in mouse stomach and human gastric cells. We show that HNF4α protein is expressed in pit (foveolar) cells, mucous neck cells, and zymogenic chief cells (ZCs) of the corpus gastric unit. Loss of HNF4α in adult mouse stomach led to reduced ZC size and ER content, phenocopying previously characterized effects of Xbp1 deletion. However, HNF4α(Δ/Δ) stomachs also exhibited additional phenotypes including increased proliferation in the isthmal stem cell zone and altered mucous neck cell migration, indicating a role of HNF4α in progenitor cells as well as in ZCs. HNF4α directly occupies the Xbp1 promoter locus in mouse stomach, and forced HNF4α expression increased abundance of XBP1 mRNA in human gastric cancer cells. Finally, as expected, loss of HNF4α caused decreased Xbp1 and Mist1 expression in mouse stomachs. We show that HNF4α regulates homeostatic proliferation in the gastric epithelium and is both necessary and sufficient for the upstream regulation of the Xbp1→Mist1 axis in maintenance of ZC secretory architecture.

PBPK modeling of irbesartan: incorporation of hepatic uptake

Physiological based pharmacokinetic (PBPK) modeling is now commonly used in drug development to integrate human or animal physiological data in order to predict pharmacokinetic profiles. The aim of this work was to construct and refine a PBPK model of irbesartan taking into account its active uptake via OATP1B1/B3 in order to predict more accurately its pharmacokinetic profile using Simcyp(®). The activity and expression of the human hepatocyte transporters OATP1B1 and OATP1B3 were studied. The relative activity factors (RAFs) for OATP1B1 and OATP1B3 transporters were calculated from intrinsic clearances obtained by concentration dependent uptake experiments in human hepatocytes and HEK overexpressing cells: RAF1B1 using estrone-3-sulfate and pitavastatine clearances, and RAF1B3 using cholecystokinine octapeptide (CCK-8) clearances. The relative expression factor (REF) was calculated by comparing immunoblotting of hepatocytes (REFHH ) or tissues (REFtissue) with those of overexpressing HEK cells for each transporter. These scaling factors were applied in a PBPK model of irbesartan using the Simcyp® simulator. Pharmacokinetic simulation using REFHH (1.82 for OATP1B1, 8.03 for OATP1B3) as an extrapolation factor was the closest to the human clinical pharmacokinetic profile of irbesartan. These investigations show the importance of integrating the contribution of the active uptake of a drug in the liver to improve PBPK modeling.