Characterization of primary human hepatocytes, HepG2 cells, and HepaRG cells at the mRNA level and CYP activity in response to inducers and their predictivity for the detection of human hepatotoxins

In the pharmaceutical industry, improving the early detection of drug-induced hepatotoxicity is essential as it is one of the most important reasons for attrition of candidate drugs during the later stages of drug development. The first objective of this study was to better characterize different cellular models (i.e., HepG2, HepaRG cells, and fresh primary human hepatocytes) at the gene expression level and analyze their metabolic cytochrome P450 capabilities. The cellular models were exposed to three different CYP450 inducers; beta-naphthoflavone (BNF), phenobarbital (PB), and rifampicin (RIF). HepG2 cells responded very weakly to the different inducers at the gene expression level, and this translated generally into low CYP450 activities in the induced cells compared with the control cells. On the contrary, HepaRG cells and the three human donors were inducible after exposure to BNF, PB, and RIF according to gene expression responses and CYP450 activities. Consequently, HepaRG cells could be used in screening as a substitute and/or in complement to primary hepatocytes for CYP induction studies. The second objective was to investigate the predictivity of the different cellular models to detect hepatotoxins (16 hepatotoxic and 5 nonhepatotoxic compounds). Specificity was 100% with the different cellular models tested. Cryopreserved human hepatocytes gave the highest sensitivity, ranging from 31% to 44% (depending on the donor), followed by lower sensitivity (13%) for HepaRG and HepG2 cells (6.3%). Overall, none of the models under study gave desirable sensitivities (80–100%). Consequently, a high metabolic capacity and CYP inducibility in cell lines does not necessarily correlate with a high sensitivity for the detection of hepatotoxic drugs. Further investigations are necessary to compare different cellular models and determine those that are best suited for the detection of hepatotoxic compounds

In situ proliferation and differentiation of macrophages in dental pulp

The presence of macrophages in dental pulp is well known. However, whether these macrophages proliferate and differentiate in the dental pulp in situ, or whether they constantly migrate from the blood stream into the dental pulp remains unknown. We have examined and compared the development of dental pulp macrophages in an organ culture system with in vivo tooth organs to clarify the developmental mechanism of these macrophages. The first mandibular molar tooth organs from ICR mice aged between 16 days of gestation (E16) to 5 days postnatally were used for in vivo experiments. Those from E16 were cultured for up to 14 days with or without 10% fetal bovine serum. Dental pulp tissues were analyzed with immunohistochemistry to detect the macrophages and with reverse transcription and the polymerase chain reaction (RT-PCR) for the detection of factors related to macrophage development. The growth curves for the in vivo and in vitro cultured cells revealed similar numbers of F4/80-positive macrophages in the dental pulp. RT-PCR analysis indicated the constant expression of myeloid colony-stimulating factor (M-CSF) in both in-vivo- and in-vitro-cultured dental pulp tissues. Anti-M-CSF antibodies significantly inhibited the increase in the number of macrophages in the dental pulp. These results suggest that (1) most of the dental pulp macrophages proliferate and differentiate in the dental pulp without a supply of precursor cells from the blood stream, (2) M-CSF might be a candidate molecule for dental pulp macrophage development, and (3) serum factors might not directly affect the development of macrophages

Evaluating Efficacy of Landsat-Derived Environmental Covariates for Predicting Malaria Distribution in Rural Villages of Vhembe District, South Africa

Malaria in South Africa is still a problem despite existing efforts to eradicate the disease. In the Vhembe District Municipality, malaria prevalence is still high, with a mean incidence rate of 328.2 per 100,0000 persons/year. This study aimed at evaluating environmental covariates, such as vegetation moisture and vegetation greenness, associated with malaria vector distribution for better predictability towards rapid and efficient disease management and control. The 2005 malaria incidence data combined with Landsat 5 ETM were used in this study. A total of nine remotely sensed covariates were derived, while pseudo-absences in the ratio of 1:2 (presence/absence) were generated at buffer distances of 0.5–20 km from known presence locations. A stepwise logistic regression model was applied to analyse the spatial distribution of malaria in the area. A buffer distance of 10 km yielded the highest classification accuracy of 82% at a threshold of 0.9. This model was significant (ρ < 0.05) and yielded a deviance (D2) of 36%. The significantly positive relationship (ρ < 0.05) between the soil-adjusted vegetation index and malaria distribution at all buffer distances suggests that malaria vector (Anopheles arabiensis) prefer productive and greener vegetation. The significant negative relationship between water/moisture index (a1 index) and malaria distribution in buffer distances of 0.5, 10, and 20 km suggest that malaria distribution increases with a decrease in shortwave reflectance signal. The study has shown that suitable habitats of malaria vectors are generally found within a radius of 10 km in semi-arid environments, and this insight can be useful to aid efforts aimed at putting in place evidence-based preventative measures against malaria infections. Furthermore, this result is important in understanding malaria dynamics under the current climate and environmental changes. The study has also demonstrated the use of Landsat data and the ability to extract environmental conditions which favour the distribution of malaria vector (An. arabiensis) such as the canopy moisture content in vegetation, which serves as a surrogate for rainfall.The South African National Space Agency under the Human Capital Development.http://link.springer.com/journal/103932019-03-01hj2018Geography, Geoinformatics and Meteorolog