Genetic toxicity testing assesses the potential of compounds to cause DNA damage. There are many genetic toxicology screening assays designed to assess the DNA damaging potential of chemicals in early drug development aiding the identification of promising drugs that have low-risk potential for causing genetic damage contributing to cancer risk in humans. Despite this, in vitro tests generate a high number of misleading positives, the consequences of which can lead to unnecessary animal testing and/or the abandonment of promising drug candidates. Understanding chemical Mode of Action (MoA) is vital to identifying the true genotoxic potential of substances and, therefore, the risk translation into the clinic. Here we demonstrate a simple, robust protocol for staining fixed, human-lymphoblast p53 proficient TK6 cells with antibodies against ɣH2AX, p53 and pH3S28 along with DRAQ5™ DNA staining that enables analysis of un-lysed cells via microscopy approaches such as imaging flow cytometry. Here, we used the Cytek® Amnis® ImageStream®X Mk II which provides a high-throughput acquisition platform with the sensitivity of flow cytometry and spatial morphological information associated with microscopy. Using the ImageStream manufacturer\'s software (IDEAS® 6.2), a masking strategy was developed to automatically detect and quantify micronucleus events (MN) and characterise biomarker populations. The gating strategy developed enables the generation of a template capable of automatically batch processing data files quantifying cell-cycle, MN, ɣH2AX, p53 and pH3 populations simultaneously. In this way, we demonstrate how a multiplex system enables DNA damage assessment alongside MN identification using un-lysed cells on the imaging flow cytometry platform. As a proof-of-concept, we use the tool chemicals carbendazim and methyl methanesulphonate (MMS) to demonstrate the assay\'s ability to correctly identify clastogenic or aneugenic MoAs using the biomarker profiles established.

A main function of dose-response assessment is to estimate a \"safe\" dose in the target population to support chemical risk assessment. Typically, a \"safe\" dose is developed differently for cancer and noncancer effects based on a 2-step procedure, ie, point of departure (POD) derivation and low-dose extrapolation. However, the current dose-response assessment framework is criticized for its dichotomized strategy without integrating the mode of action (MOA) information. The objective of this study was, based on our previous work, to develop a MOA-based probabilistic dose-response framework that quantitatively synthesizes a biological pathway in a dose-response modeling process to estimate the risk of chemicals that have carcinogenic potential. 3,3\',4,4\',5-Pentachlorobiphenyl (PCB-126) was exemplified to demonstrate our proposed approach. There were 4 major steps in the new modeling framework, including (1) key quantifiable events (KQEs) identification and extraction, (2) essential dose calculation, (3) MOA-based POD derivation, and (4) MOA-based probabilistic reference dose (RfD) estimation. Compared with reported PODs and traditional RfDs, the MOA-based estimates derived from our approach were comparable and plausible. One key feature of our approach was the use of overall MOA information to build the dose-response relationship on the entire dose continuum including the low-dose region. On the other hand, by adjusting uncertainty and variability in a probabilistic manner, the MOA-based probabilistic RfDs can provide useful insights of health protection for the specific proportion of population. Moreover, the proposed framework had important potential to be generalized to assess different types of chemicals other than nonmutagenic carcinogens, highlighting its utility to improve current chemical risk assessment.

BACKGROUND: Although Deep Neural Networks (DDNs) have been successful in predicting the efficacy of cancer drugs, the lack of explainability in their decision-making process is a significant challenge. Previous research proposed mimicking the Gene Ontology structure to allow for interpretation of each neuron in the network. However, these previous approaches require huge amount of GPU resources and hinder its extension to genome-wide models.
METHODS: We developed SparseGO, a sparse and interpretable neural network, for predicting drug response in cancer cell lines and their Mechanism of Action (MoA). To ensure model generalization, we trained it on multiple datasets and evaluated its performance using three cross-validation schemes. Its efficiency allows it to be used with gene expression. In addition, SparseGO integrates an eXplainable Artificial Intelligence (XAI) technique, DeepLIFT, with Support Vector Machines to computationally discover the MoA of drugs.
RESULTS: SparseGO\'s sparse implementation significantly reduced GPU memory usage and training speed compared to other methods, allowing it to process gene expression instead of mutations as input data. SparseGO using expression improved the accuracy and enabled its use on drug repositioning. Furthermore, gene expression allows the prediction of MoA using 265 drugs to train it. It was validated on understudied drugs such as parbendazole and PD153035.
CONCLUSIONS: SparseGO is an effective XAI method for predicting, but more importantly, understanding drug response.
BACKGROUND: The Accelerator Award Programme funded by Cancer Research UK [C355/A26819], Fundación Científica de la AECC and Fondazione AIRC, Project PIBA_2020_1_0055 funded by the Basque Government and the Synlethal Project (RETOS Investigacion, Spanish Government).

Heterogeneous catalysis composed of plasmonic metal and semiconductor has been utilized to tune local surface electron density in MOA (Molecular oxygen activation). However, there is a severe antagonistic effect between Schottky junction carriers and SPR (Surface Plasmon Resonance) induced hot carriers transfer routers when metal and semiconductor are both excited to dramatically reduce carriers separation efficiency. Hence, a highly effective photocatalytic antifoulant obtained by V-CN (carbon nitride with nitrogen vacancies) in-situ loading Cu2O and Ag nanoparticles (Cu2O/Ag/V-CN) was introduced to promote MOA to assist the metal ions sterilization. The DFT calculations (Density Functional Theory) and FEM calculations (Finite Element Method) intuitively proved the photocatalytic antifoulant belonged to a ternary Z-scheme heterojunction and could visibly weaken the antagonistic effect of hot carriers and Schottky carriers transport routes. The delocalized electron structure caused by V-CN and the effective electron mediator of Ag were the key to the formation of Z-scheme interfacial heterojunctions. These conclusions were also supported by experimental data, like more ∙O2- production capacity, efficient carriers separation, and higher carriers lifetime (27% higher than Cu2O and Cu2O/V-CN) as well as the weakened Cu2O photocorrosion tendency (Cu2O turning into CuO). Additionally, except for increasing nearly-three times adsorption energy of O2 for rapid activation, Cu2O/Ag/V-CN with abundant nitrogen vacancies can more significantly slow metal ions release (less about 97% to pure Cu2O and at least 22% higher than reported systems), which can observably save the amount of catalyst and heavy metals content. Therefore, Cu2O/Ag/V-CN has great potential for practical antifouling applications.

The aim of this study is to define chemical categories that can be applied to regulatory read-across assessments for repeated-dose toxicity, by classifying toxic substances based on their structures and mechanism of actions (MoAs). Hemolytic anemia, which often appears primarily, was examined as an example. An integrated database was constructed by collecting publicly available datasets on repeated-dose toxicity, in which 423 out of a total of 1518 chemicals were identified as capable of inducing hemolytic anemia. Subsequently, by grouping these chemicals based on their chemical structures and plausible MoAs on hemolytic substances, we identified the following categories: (i) anilines, (ii) nitrobenzenes, (iii) nitroanilines, (iv) dinitroanilines, (v) ethylene glycol alkyl ethers, (vi) hydroquinones, (vii) oximes, and (viii) hydrazines. In these categories, the toxicant and the measurable key events leading to hematotoxicity were identified, thereby allowing us to justify the categories and to discriminate the category substances. Moreover, toxicokinetics seems to critically affect the hemolytic levels of the category substances. Overall, the categories were validated through a comprehensive analysis of the collected information, while the utility was demonstrated by conducting a case study on the selected category. Further endeavors with this approach would attain categories for other organ toxicity endpoints.

Flumioxazin, is a herbicide that has inhibitory activity on protoporphyrinogen oxidase (PPO), a key enzyme in the biosynthetic pathway for heme. Flumioxazin induces anemia and developmental toxicity in rats, including ventricular septal defect and embryofetal death. Studies to elucidate the mode of action (MOA) of flumioxazin as a developmental toxicant and to evaluate its relevance to humans have been undertaken. The MOA in the rat has now been elucidated. The first key event is PPO inhibition, which results in reduced heme synthesis in embryonic erythroblasts. The critical window for this effect is gestational day 12 when almost all erythroblasts are at the polychromatophilic stage, synthesizing heme very actively. Embryonic anemia/hypoxemia is induced and the heart pumps more strongly as a compensatory action during organogenesis, leading to thinning of the ventricular walls and failure of the interventricular septum to build completely and close. Investigations showed that this MOA is specific to rats and has no relevancy to humans. Flumioxazin inhibited PPO in rat hepatocyte mitochondria more strongly than in human. A 3-dimensional molecular simulation revealed that species differences in binding affinity of flumioxazin to PPO, observed previously in vitro, were due to differences in binding free energy. In vitro studies using several types of rat and human cells (erythroblasts derived from erythroleukemia cell lines, cord blood, or pluripotent stem cells), showed that flumioxazin decreased heme synthesis in rat cells but not in human cells, demonstrating a clear, qualitative species difference. Considering all available information, including data from PBPK modelling in rat and human, as well as the fact that anemia is not a symptom in patients with variegate porphyria, a congenital hereditary PPO defect, shows that the sequence of events leading to adverse effects in the rat embryo and fetus are very unlikely to occur in humans.

Herein, we report the preparation of a panel of Schiff bases analogues as antiprotozoal agents by modification of the stereoelectronic effects of the substituents on N-1 and N-4 and the nature of the chalcogen atom (S, Se). These compounds were evaluated towards Trypanosoma cruzi and Trichomonas vaginalis. Thiosemicarbazide 31 showed the best trypanocidal profile (epimastigotes), similar to benznidazole (BZ): IC50 (31)=28.72 μM (CL-B5 strain) and 33.65 μM (Y strain), IC50 (BZ)=25.31 μM (CL-B5) and 22.73 μM (Y); it lacked toxicity over mammalian cells (CC50 > 256 µM). Thiosemicarbazones 49, 51 and 63 showed remarkable trichomonacidal effects (IC50 =16.39, 14.84 and 14.89 µM) and no unspecific cytotoxicity towards Vero cells (CC50 ≥ 275 µM). Selenoisosters 74 and 75 presented a slightly enhanced activity (IC50=11.10 and 11.02 µM, respectively). Hydrogenosome membrane potential and structural changes were analysed to get more insight into the trichomonacidal mechanism.

HBI-8000 is a small molecule inhibitor of class I HDACs and has been approved for the treatment of PTCL, ATL and, in combination with exemestane, in a subpopulation of breast cancer. Given the roles of HDACs in normal and cancerous cells, there are currently multiple clinical trials, by HUYABIO International, to test the efficacy of HBI-8000 in monotherapy or in combination settings in leukemias and in solid tumors. The current review is focused on the applications of HDACi HBI-8000 in cancer therapy and its potential in combination with DDR agents.

Assessment of genotoxicity is a critical component of mode of action (MOA) analysis and carcinogen risk assessment due to its influence on quantitative risk extrapolation approaches. To date, clear guidance and expert consensus on the determination of a mutagenic MOA remains elusive, resulting in different estimates of carcinogenic risk for the same chemical among different stakeholders. Oral toxicity criteria for hexavalent chromium [Cr(VI)], for example, differ by orders of magnitude due largely to the interpretation of in vivo genotoxicity data. Herein, we review in vivo genotoxicity studies for Cr(VI) to inform the MOA for Cr(VI)-induced tumors observed in a two-year cancer bioassay in mice and rats exposed via drinking water. Overall, genotoxicity results in carcinogenic target tissues (viz., oral cavity and duodenum) are negative. Results in the intestine are consistent with imaging data indicating little to no chromium present in the crypt compartment following oral exposure. Positive genotoxicity results in nontarget tissues have been reported at high doses mostly following nonphysiological routes of exposure. Given the negative genotoxicity results in carcinogenic target organs from oral exposure to Cr(VI), there is scientific justification to support the use of nonlinear low-dose extrapolation methods in the derivation of oral toxicity criteria for Cr(VI). These results highlight important differences between genotoxicity testing for hazard identification purposes and quantitative risk assessment.

In view of the demand of location awareness in a special complex environment, for an unmanned aerial vehicle (UAV) airborne multi base-station semi-passive positioning system, the hybrid positioning solutions and optimized site layout in the positioning system can effectively improve the positioning accuracy for a specific region. In this paper, the geometric dilution of precision (GDOP) formula of a time difference of arrival (TDOA) and angles of arrival (AOA) hybrid location algorithm is deduced. Mayfly optimization algorithm (MOA) which is a new swarm intelligence optimization algorithm is introduced, and a method to find the optimal station of the UAV airborne multiple base station\'s semi-passive positioning system using MOA is proposed. The simulation and analysis of the optimization of the different number of base stations, compared with other station layout methods, such as particle swarm optimization (PSO), genetic algorithm (GA), and artificial bee colony (ABC) algorithm. MOA is less likely to fall into local optimum, and the error of regional target positioning is reduced. By simulating the deployment of four base stations and five base stations in various situations, MOA can achieve a better deployment effect. The dynamic station configuration capability of the multi-station semi-passive positioning system has been improved with the UAV.