The liver is among the most frequently targeted organs by noxious chemicals of diverse nature. Liver toxicity testing using laboratory animals not only raises serious ethical questions, but is also rather poorly predictive of human safety towards chemicals. Increasing attention is, therefore, being paid to the development of non-animal and human-based testing schemes, which rely to a great extent on in vitro methodology. The present paper proposes a rationalized tiered in vitro testing strategy to detect liver toxicity triggered by chemicals, in which the first tier is focused on assessing general cytotoxicity, while the second tier is aimed at identifying liver-specific toxicity as such. A state-of-the-art overview is provided of the most commonly used in vitro assays that can be used in both tiers. Advantages and disadvantages of each assay as well as overall practical considerations are discussed.

Connexin and pannexin (hemi)channels play an important role in paracrine and autocrine signaling pathways. The opening of these cellular pores is linked to a wide range of diseases. Therefore, phar...

Although many efforts have been made to elucidate the pathogenesis of COVID-19, the underlying mechanisms are yet to be fully uncovered. However, it is known that a dysfunctional immune response and the accompanying uncontrollable inflammation lead to troublesome outcomes in COVID-19 patients. Pannexin1 channels are put forward as interesting drug targets for the treatment of COVID-19 due to their key role in inflammation and their link to other viral infections. In the present study, we selected a panel of drugs previously tested in clinical trials as potential candidates for the treatment of COVID-19 early on in the pandemic, including hydroxychloroquine, chloroquine, azithromycin, dexamethasone, ribavirin, remdesivir, favipiravir, lopinavir, and ritonavir. The effect of the drugs on pannexin1 channels was assessed at a functional level by means of measurement of extracellular ATP release. Immunoblot analysis and real-time quantitative reversetranscription polymerase chain reaction analysis were used to study the potential of the drugs to alter pannexin1 protein and mRNA expression levels, respectively. Favipiravir, hydroxychloroquine, lopinavir, and the combination of lopinavir with ritonavir were found to inhibit pannexin1 channel activity without affecting pannexin1 protein or mRNA levels. Thusthree new inhibitors of pannexin1 channels were identified that, though currently not being used anymore for the treatment of COVID-19 patients, could be potential drug candidates for other pannexin1-related diseases.

Connexin43 (Cx43) hemichannels form a pathway for cellular communication between the cell and its extracellular environment. Under pathological conditions, Cx43 hemichannels release adenosine triphosphate (ATP), which triggers inflammation. Over the past two years, azithromycin, chloroquine, dexamethasone, favipiravir, hydroxychloroquine, lopinavir, remdesivir, ribavirin, and ritonavir have been proposed as drugs for the treatment of the coronavirus disease 2019 (COVID-19), which is associated with prominent systemic inflammation. The current study aimed to investigate if Cx43 hemichannels, being key players in inflammation, could be affected by these drugs which were formerly designated as COVID-19 drugs. For this purpose, Cx43-transduced cells were exposed to these drugs. The effects on Cx43 hemichannel activity were assessed by measuring extracellular ATP release, while the effects at the transcriptional and translational levels were monitored by means of real-time quantitative reverse transcriptase polymerase chain reaction analysis and immunoblot analysis, respectively. Exposure to lopinavir and ritonavir combined (4:1 ratio), as well as to remdesivir, reduced Cx43 mRNA levels. None of the tested drugs affected Cx43 protein expression.

Background: Using a randomized, double blind, placebo-controlled, crossover protocol, we have shown previously that progesterone may prevent sleep disturbances but has no action on undisturbed sleep. In that study, 8 healthy postmenopausal women took daily at 2300 h for 3 wk a capsule of either 300 mg of progesterone or placebo. Sleep was polygraphically recorded during the last two nights and, during the second night, blood samples were collected at 15-min intervals using an iv catheter,. During the first night, sleep was normal under placebo and progesterone had no effect. During the second night, blood sampling procedure was associated under placebo with marked sleep disturbances, which were considerably reduced under progesterone: at the group level, mean ± SEM duration of wake after sleep onset (WASO) dropped from 152 ± 37 min to 71 ± 19 min (P = 0.01), and slow-wave sleep (SWS) duration increased from 53 ± 6 min to 79 ± 10 min (P = 0.04). Objective: To submit individual data collected in that study to new analyses designed to further investigate possible mechanism(s) of progesterone actions on sleep architecture. Results: Among individual subjects, no relation could be evidenced between progesterone levels and sleep variables, or between individual progesterone-associated improvements and absolute values of corresponding sleep variables under placebo. By contrast, for WASO and SWS, significant positive correlations (Spearman test) were evidenced between individual responses to progesterone (i.e. the difference, during night 2, between value under progesterone and value under placebo) and corresponding individual alterations caused under placebo by the blood sampling procedure (i.e. the difference, under placebo, between value during night 1 and value during night 2): WASO: r_s = 0.74, P = 0.037, n = 8; SWS: r_s = 0.86, P = 0.014, n = 7. (Pearson test yielded similar results: WASO: r = 0.85, P = 0.008; SWS: r = 0.76, P = 0.047). Conclusions: Although they obviously need to be confirmed by larger studies performed in a variety of clinical conditions, the present findings suggest that progesterone action on sleep architecture is specifically tailored to restore individual normality rather than group normality. Since SWS is mainly regulated by the sleep-wake homeostatic mechanism relating sleep pressure to the duration of prior wakefulness, it is tempting to speculate that progesterone might be an active component of this mechanism.