Betulinic Acid–Doxorubicin-Drug combination induced apoptotic death via ROS stimulation in a relapsed AML MOLM-13 cell model

In this study, cell death regulation and induction in AML cell line from a relapsed MLL-rearranged cell model (MOLM-13) was investigated with doxorubin (Dox) and betulinic acid (BetA), singly and in combination. CyQUANT Direct® and Annexin V/propidium iodide double staining were used to measure the cytotoxic and cell death induction effects of the compounds, respectively. Reactive oxygen species (ROS) generation was measured using 2′,7′-dichlorofluorescin diacetate staining. Expressions of proteins and genes were examined by Western blot and reverse transcription polymerase chain reaction analysis, respectively. BetA (20 μM) and Dox (1 μM) indicated a synergistic growth inhibitory effect on MOLM-13 cells. The combined drug caused more cells to reside in irreversible late apoptotic stage compared to the single treatments (p < 0.05). Elevation in ROS may be the synergistic mechanism involved in MOLM-13 cell death since ROS can directly disrupt mitochondrial activity. In contrast, in leukaemic U-937 cells, the combination treatments attenuated Dox-induced cell death. Dox and the drug combination selectively reduced (p < 0.05) a recently reported anti-apoptotic Bcl-2 protein isoform p15-20-Bcl-2 in MOLM-13 by our group, without affecting the usually reported p26-Bcl-2-α. Further studies using known inhibitors of apoptosis are required to confirm the potential of Dox-BetA combination to modulate these pathways

The mouse alpha-globin cluster: A paradigm for studying genome regulation and organization

The mammalian globin gene clusters provide a paradigm for studying the relationship between genome structure and function. As blood stem cells undergo lineage specification and differentiation to form red blood cells, the chromatin structure and expression of the α-globin cluster change. The gradual activation of the α-globin genes in well-defined cell populations has enabled investigation of the structural and functional roles of its enhancers, promoters and boundary elements. Recent studies of gene regulatory processes involving these elements at the mouse α-globin cluster have brought new insights into the general principles underlying the three-dimensional structure of the genome and its relationship to gene expression throughout time

Doxorubicin selectively induces apoptosis through the inhibition of a novel isoform of Bcl‑2 in acute myeloid leukaemia MOLM‑13 cells with reduced Beclin 1 expression

The overexpression of anti-apoptotic Bcl-2 in acute myeloid leukaemia (AML) may contribute to difficulties in eradicating these cells during chemotherapy. In the present study, doxorubicin (Dox) was evaluated for its potential to induce selective apoptotic cell death in AML MOLM-13 cells and to modulate autophagy through Bcl-2 and Beclin 1 protein expression. Annexin V/propidium iodide and 5(6)-carboxyfluorescein diacetate succinimidyl ester (CFSE) flow cytometric analyses were conducted to determine the effects of Dox on cell death and cell proliferation, respectively, following 48 h of co-incubation with AML MOLM-13 or U-937 monocytic cells. The protein expression levels of Bcl-2 and Beclin 1 in untreated and treated cells were quantified by western blot analysis. Dox reduced the viability of MOLM-13 cells partly by inhibiting cell division and inducing cell apoptosis. Dox demonstrated a level of selectivity in its cytotoxicity against MOLM-13 compared to U-937 cells (P<0.05). Dox induced a significant decrease in Beclin 1 protein levels in MOLM-13 cells without significantly affecting the protein levels in U-937 monocytes. A novel Bcl-2 15-20 kDa (p15-20-Bcl-2) isoform was found to be selectively expressed in AML MOLM-13 cells (but absent in the leukaemic cell lines tested, OCI-AML2, CML K562 and U-937). Dox induced a highly significant inhibition of p15-20-Bcl-2 at concentrations of 0.5, 0.75 and 1 µM (P<0.01). However, the usual 26 kDa Bcl-2 (p26-Bcl-2-α) isoform protein expression was not affected by the drug in either the MOLM-13 or U-937 cells. It was thus postulated that Dox exhibited some selectivity by targeting the p15-20-Bcl-2 isoform in MOLM-13 cells and activating Beclin 1 to induce cell death

Mitochondrial protein-linked DNA breaks perturb mitochondrial gene transcription and trigger free radical-induced DNA damage

Breakage of one strand of DNA is the most common form of DNA damage. Most damaged DNA termini require end processing in preparation for ligation. The importance of this step is highlighted by the association of defects in the 3'-end processing enzyme tyrosyl DNA phosphodiesterase 1 (TDP1) and neurodegeneration, and by the cytotoxic induction of protein-linked DNA breaks (PDBs) and oxidised nucleic acid intermediates during chemo- and radiotherapy. Although much is known about the repair of PDBs in the nucleus, little is known about this process in the mitochondria. Here, we reveal that TDP1 resolves mitochondrial PDBs (mtPDBs), thereby promoting mitochondrial gene transcription. In the absence of TDP1, the imbalance in transcription of mitochondrial and nuclear encoded electron transport chain (ETC) subunits results in misassembly of the ETC complex III. Bioenergetics profiling further reveals that TDP1 promotes oxidative phosphorylation under both basal and high ATP demands. Mitochondrial dysfunction results in free radical leakage and nuclear DNA damage. Consequently, we report an increased accumulation of carbon-centred radicals in cells lacking TDP1, using electron spin resonance spectroscopy. Overexpression of the anti-oxidant enzyme superoxide dismutase 1 (SOD1) reduces carbon-centred adducts and protects TDP1 deficient cells from oxidative stress. Conversely, overexpression of the amyotrophic lateral sclerosis (ALS)-associated mutant SOD1G93A leads to marked sensitivity. Together, this data characterises a novel TDP1 driven mitochondrial PDB repair process and unravels its role in promoting mitochondrial gene transcription and oxygen consumption by oxidative phosphorylation, thus conferring cellular protection against ROS induced damage

UVA-induced carbon-centered radicals in lightly pigmented cells detected using ESR spectroscopy

Ultraviolet-A and melanin are implicated in melanoma, but whether melanin in vivo screens or acts as a UVA photosensitiser is debated. Here, we investigate the effect of UVA-irradiation on non-pigmented, lightly and darkly pigmented melanocytes and melanoma cells using electron spin resonance (ESR) spectroscopy. Using the spin trap 5,5 Dimethyl-1-pyrroline N-oxide (DMPO), carbon adducts were detected in all cells. However, higher levels of carbon adducts were detected in lightly pigmented cells than in non-pigmented or darkly pigmented cells. Nevertheless, when melanin levels were artificially increased in lightly pigmented cells by incubation with L-Tyrosine, the levels of carbon adducts decreased significantly. Carbon adducts were also detected in UVA-irradiated melanin-free cell nuclei, DNA-melanin systems, and the nucleoside 2’-deoxyguanosine combined with melanin, whereas they were only weakly detected in irradiated synthetic melanin and not at all in irradiated 2’-deoxyguanosine. The similarity of these carbon adducts suggests they may be derived from nucleic acid– guanine – radicals. These observations suggest that melanin is not consistently a UVA screen against free-radical formation in pigmented cells, but may also act as a photosensitizer for the formation of nucleic acid radicals in addition to superoxide. The findings are important for our understanding of the mechanism of damage caused by the UVA component of sunlight in non-melanoma and melanoma cells, and hence the causes of skin cancer

Hybrid in vitro diffusion cell for simultaneous evaluation of hair and skin decontamination: temporal distribution of chemical contaminants

Most casualty or personnel decontamination studies have focused on removing contaminants from the skin. However, scalp hair and underlying skin are the most likely areas of contamination following airborne exposure to chemicals. The aim of this study was to investigate the interactions of contaminants with scalp hair and underlying skin using a hybrid in vitro diffusion cell model. The in vitro hybrid test system comprised “curtains” of human hair mounted onto sections of excised porcine skin within a modified diffusion cell. The results demonstrated that hair substantially reduced underlying scalp skin contamination and that hair may provide a limited decontamination effect by removing contaminants from the skin surface. This hybrid test system may have application in the development of improved chemical incident response processes through the evaluation of various hair and skin decontamination strategies.Peer reviewedFinal Published versio

Towards cyber-resilient telecontrol commands using software-defined networking

Cybersecurity enhancement of power systems has become one of the main objectives of utility managers and regulatory agencies because of the increasing number of cyberattacks against critical infrastructures. In this paper, we investigate the application of software-defined networking for improving the cyber-resilience of power systems in the presence of cyberattacks using false telecontrol commands. It is first demonstrated that cyberattackers can use false telecontrol commands to separate a power plant from a power grid or trip a major transmission line. Next, it is shown that software-defined networking can significantly enhance the cyber-resilience of power systems in the presence of cyberattacks using false telecontrol commands compared to legacy communication networks. This is because the source, destination and protocol of telecontrol commands can be examined and verified in software-defined networking before communication packet forwarding actions take place. Moreover, primary and back-up routes of telecontrol commands can be pre-engineered in software-defined networking to counteract potential cyberattacks

Cybersecurity Enhancement of Transformer Differential Protection Using Machine Learning

The growing use of information and communication technologies (ICT) in power grid operational environments has been essential for operators to improve the monitoring, maintenance and control of power generation, transmission and distribution, however, at the expense of an increased grid exposure to cyber threats. This paper considers cyberattack scenarios targeting substation protective relays that can form the most critical ingredient for the protection of power systems against abnormal conditions. Disrupting the relays operations may yield major consequences on the overall power grid performance possibly leading to widespread blackouts. We investigate methods for the enhancement of substation cybersecurity by leveraging the potential of machine learning for the detection of transformer differential protective relays anomalous behavior. The proposed method analyses operational technology (OT) data obtained from the substation current transformers (CTs) in order to detect cyberattacks. Power systems simulation using OPAL-RT HYPERSIM is used to generate training data sets, to simulate the cyberattacks and to assess the cybersecurity enhancement capability of the proposed machine learning algorithms

A Deep Learning-Based Cyberattack Detection System for Transmission Protective Relays

The digitalization of power systems over the past decade has made the cybersecurity of substations a top priority for regulatory agencies and utilities. Proprietary communication protocols are being increasingly replaced by standardized and interoperable protocols providing utility operators with remote access and control capabilities at the expense of growing cyberattack risks. In particular, the potential of supply chain cyberattacks is on the rise in industrial control systems. In this environment, there is a pressing need for the development of cyberattack detection systems for substations and in particular protective relays, a critical component of substation operation. This paper presents a deep learning-based cyberattack detection system for transmission line protective relays. The proposed cyberattack detection system is first trained with current and voltage measurements representing various types of faults on the transmission lines. The cyberattack detection system is then employed to detect current and voltage measurements that are maliciously injected by an attacker to trigger the transmission line protective relays. The proposed cyberattack detection system is evaluated under a variety of cyberattack scenarios. The results demonstrate that a universal architecture can be designed for the deep learning-based cyberattack detection systems in substations