Corrigendum to "Curcumin protects rat liver from streptozotocin-induced diabetic pathophysiology by counteracting reactive oxygen species and inhibiting the activation of p53 and MAPKs mediated stress response pathways" [Toxicol. Rep. 2 (2015) 365-376]

[This corrects the article DOI: 10.1016/j.toxrep.2014.12.017.].

Biological evaluation of the novel 3,3'-((4-nitrophenyl)methylene)bis(4-hydroxy-2H-chromen-2-one) derivative as potential anticancer agents via the selective induction of reactive oxygen species-mediated apoptosis

Selective initiation of programmed cell death in cancer cells than normal cells is reflected as an attractive chemotherapeutic strategy. In the current study, a series of synthetic bis-coumarin derivatives were synthesized possessing reactive oxygen species (ROS) modulating functional groups and examined in four cancerous and two normal cell lines for their cytotoxic ability using MTT assay. Among these compounds, 3 l emerged as the most promising derivative in persuading apoptosis in human renal carcinoma cells (SKRC-45) among diverse cancer cell lines. 3 l causes significantly less cytotoxicity to normal kidney cells compared to cisplatin. This compound was able to induce apoptosis and cell-cycle arrest by modulating the p53 mediated apoptotic pathways via the generation of ROS, decreasing mitochondrial membrane potential, and causing DNA fragmentation. Unlike cisplatin, the 3 l derivative was found to inhibit the nuclear localisation of NF-κB in SKRC-45 cells. It was also found to reduce the proliferation, survival and migration ability of SKRC-45 cells by downregulating COX-2/ PTGES2 cascade and MMP-2. In an in vivo tumor model, 3 l showed an anticancer effect by reducing the mean tumor mass, volume and inducing caspase-3 activation, without affecting kidney function. Further studies are needed to establish 3 l as a promising anti-cancer drug candidate.

A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies

Drug toxicity prediction is an important step in ensuring patient safety during drug design studies. While traditional preclinical studies have historically relied on animal models to evaluate toxicity, recent advances in deep-learning approaches have shown great promise in advancing drug safety science and reducing animal use in preclinical studies. However, deep-learning-based approaches also face challenges in handling large biological data sets, model interpretability, and regulatory acceptance. In this review, we provide an overview of recent developments in deep-learning-based approaches for predicting drug toxicity, highlighting their potential advantages over traditional methods and the need to address their limitations. Deep-learning models have demonstrated excellent performance in predicting toxicity outcomes from various data sources such as chemical structures, genomic data, and high-throughput screening assays. The potential of deep learning for automated feature engineering is also discussed. This review emphasizes the need to address ethical concerns related to the use of deep learning in drug toxicity studies, including the reduction of animal use and ensuring regulatory acceptance. Furthermore, emerging applications of deep learning in drug toxicity prediction, such as predicting drug-drug interactions and toxicity in rare subpopulations, are highlighted. The integration of deep-learning-based approaches with traditional methods is discussed as a way to develop more reliable and efficient predictive models for drug safety assessment, paving the way for safer and more effective drug discovery and development. Overall, this review highlights the critical role of deep learning in predictive toxicology and drug safety evaluation, emphasizing the need for continued research and development in this rapidly evolving field. By addressing the limitations of traditional methods, leveraging the potential of deep learning for automated feature engineering, and addressing ethical concerns, deep-learning-based approaches have the potential to revolutionize drug toxicity prediction and improve patient safety in drug discovery and development.

Isorhamnetin exerts anti-tumor activity in DEN + CCl4-induced HCC mice

BACKGROUND

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer and the main cause of cancer death globally. The use of medicinal herbs as chemotherapeutic agents in cancer treatment is receiving attention as they possess no or minimum side effects. Isorhamnetin (IRN), a flavonoid, has been under attention for its anti-inflammatory and anti-proliferative properties in a number of cancers, including colorectal, skin, and lung cancers. However, the in vivo mechanism of isorhamnetin to suppress liver cancer has yet to be explored.

METHODS AND RESULT

HCC was induced by N-diethylnitrosamine (DEN) and carbon tetrachloride (CCL₄) in Swiss albino mice. Isorhamnetin (100 mg/kg body weight) was given to examine its anti-tumor properties in HCC mice model. Histological analysis and liver function assays were performed to assess changes in liver anatomy. Probable molecular pathways were explored using immunoblot, qPCR, ELISA, and immunohistochemistry techniques. Isorhamnetin inhibited various pro-inflammatory cytokines to suppress cancer-inducing inflammation. Additionally, it regulated Akt and MAPKs to suppress Nrf2 signaling. Isorhamnetin activated PPAR-γ and autophagy while suppressing cell cycle progression in DEN + CCl₄-administered mice. Additionally, isorhamnetin regulated various signaling pathways to suppress cell proliferation, metabolism, and epithelial-mesenchymal transition in HCC.

CONCLUSION

Regulating diverse cellular signaling pathways makes isorhamnetin a better anti-cancer chemotherapeutic candidate in HCC. Importantly, the anti-TNF-α properties of isorhamnetin could prove it a valuable therapeutic agent in sorafenib-resistant HCC patients. Additionally, anti-TGF-β properties of isorhamnetin could be utilized to reduce the EMT-inducing side effects of doxorubicin.

pH-responsive and targeted delivery of chrysin via folic acid-functionalized mesoporous silica nanocarrier for breast cancer therapy

Cancer is a disease of global importance. In order to mitigate conventional chemotherapy-related side effects, phytochemicals with inherent anticancer efficacy have been opted. However, the use of nanotechnology is essential to enhance the bioavailability and therapeutic efficacy of these phytochemicals. Herein, we have formulated folic acid conjugated polyacrylic acid capped mesoporous silica nanoparticles (∼47.6 nm in diameter) for pH-dependent targeted delivery of chrysin to breast cancer (MCF-7) cells. Chrysin loaded mesoporous silica nanoparticles (Chr- mSiO2@PAA/FA) have been noted to induce apoptosis in MCF-7 cells through oxidative insult and mitochondrial dysfunction with subsequent G1 arrest. Further, in tumor bearing mice, intravenous incorporation of Chr-mSiO2@PAA/FA has been noticed to enhance the anti-neoplastic effects of chrysin via tumor site-specific accumulation. Enhanced cytotoxicity of chrysin contributed towards in vivo tumor regression, restoration of normalized tissue architecture and maintenance of healthy body weight. Besides, no serious systemic toxicity was manifested in response to Chr-mSiO2@PAA/FA administration in vivo. Thus, the study evokes about the anticancer potentiality of chrysin and its increased therapeutic activity via incorporation into folic acid conjugated mesoporous silica nanoparticles, which may hold greater impact in field of future biomedical research.

Glycobiology of cellular expiry: Decrypting the role of glycan-lectin regulatory complex and therapeutic strategies focusing on cancer

Often the outer leaflets of living cells bear a coat of glycosylated proteins, which primarily regulates cellular processes. Glycosylation of such proteins occurs as part of their post-translational modification. Within the endoplasmic reticulum, glycosylation enables the attachment of specific oligosaccharide moieties such as, 'glycan' to the transmembrane receptor proteins which confers precise biological information for governing the cell fate. The nature and degree of glycosylation of cell surface receptors are regulated by a bunch of glycosyl transferases and glycosidases which fine-tune attachment or detachment of glycan moieties. In classical death receptors, upregulation of glycosylation by glycosyl transferases is capable of inducing cell death in T cells, tumor cells, etc. Thus, any deregulated alternation at surface glycosylation of these death receptors can result in life-threatening disorder like cancer. In addition, transmembrane glycoproteins and lectin receptors can transduce intracellular signals for cell death execution. Exogenous interaction of lectins with glycan containing death receptors signals for cell death initiation by modulating downstream signalings. Subsequently, endogenous glycan-lectin interplay aids in the customization and implementation of the cell death program. Lastly, the glycan-lectin recognition system dictates the removal of apoptotic cells by sending accurate signals to the extracellular milieu. Since glycosylation has proven to be a biomarker of cellular death and disease progression; glycans serve as specific therapeutic targets of cancers. In this context, we are reviewing the molecular mechanisms of the glycan-lectin regulatory network as an integral part of cell death machinery in cancer to target them for successful therapeutic and clinical approaches.

Machine Learning in Drug Metabolism Study

Metabolic reactions in the body transform the administered drug into metabolites. These metabolites exhibit diverse biological activities. Drug metabolism is the major underlying cause of drug overdose-related toxicity, adversative drug effects and the drug's reduced efficacy. Though metabolic reactions deactivate a drug, drug metabolites are often considered pivotal agents for off-target effects or toxicity. On the other side, in combination drug therapy, one drug may influence another drug's metabolism and clearance and is thus considered one of the primary causes of drug-drug interactions. Today with the advancement of machine learning, the metabolic fate of a drug candidate can be comprehensively studied throughout the drug development procedure. Naïve Bayes, Logistic Regression, k-Nearest Neighbours, Decision Trees, different Boosting and Ensemble methods, Support Vector Machines and Artificial Neural Network boosted Deep Learning are some machine learning algorithms which are being extensively used in such studies. Such tools are covering several attributes of drug metabolism, with an emphasis on the prediction of drug-drug interactions, drug-target-interactions, clinical drug responses, metabolite predictions, sites of metabolism, etc. These reports are crucial for evaluating metabolic stability and predicting prospective drug-drug interactions, and can help pharmaceutical companies accelerate the drug development process in a less resource-demanding manner than what in vitro studies offer. It could also help medical practitioners to use combinatorial drug therapy in a more resourceful manner. Also, with the help of the enormous growth of deep learning, traditional fields of computational drug development like molecular interaction fields, molecular docking, quantitative structure-to-activity relationship (QSAR) studies and quantum mechanical simulations are producing results which were unimaginable couple of years back. This review provides a glimpse of a few contextually relevant machine learning algorithms and then focuses on their outcomes in different studies.

Synthesis, characterization, and evaluation of in vitro cytotoxicity and in vivo antitumor activity of asiatic acid-loaded poly lactic-co-glycolic acid nanoparticles: A strategy of treating breast cancer

Asiatic acid (AA), an aglycone of pentacyclic triterpene glycoside, obtained from the leaves of Centella asiatica exerts anticancer effects by inhibiting cellular proliferation and inducing apoptosis in a wide range of carcinogenic distresses. However, its chemotherapeutic efficacy is dampened by its low bioavailability. Polymeric nanoparticles (NPs) exhibit therapeutic efficacy and compliance by improving tissue penetration and lowering toxicity. Thus, to increase the therapeutic effectiveness of AA in the treatment of breast cancer, AA-loaded poly lactic-co-glycolic acid (PLGA) NPs (AA-PLGA NPs) have been formulated. The AA-PLGA NPs were characterized on the basis of their average particle size, zeta potential, electron microscopic imaging, drug loading, and entrapment efficiency. The NPs exhibited sustained drug release profile in vitro. Developed NPs exerted dose-dependent cytotoxicity to MCF-7 and MDA-MB-231 cells without damaging normal cells. The pro-oxidant and pro-apoptotic properties of AA-PLGA NPs were determined by the study of the cellular levels of SOD, CAT, GSH-GSSG, MDA, protein carbonylation, ROS, mitochondrial membrane potential, and FACS analyses on MCF-7 cells. Immunoblotting showed that AA-PLGA NPs elicited an intrinsic pathway of apoptosis in MCF-7 cells. In vivo studies on female BALB/c mice exhibited reduced volume of mammary pad tumor tissues and augmented expression of caspase-3 when administered with AA-PLGA NPs. No systemic adverse effect of AA-PLGA NPs was observed in our studies. Thus, AA-PLGA NPs can act as an efficient drug delivery system against breast cancer.

Carnosic acid attenuates doxorubicin-induced cardiotoxicity by decreasing oxidative stress and its concomitant pathological consequences

This work aimed to reveal the protective mechanism of CA against Dox (doxorubicin)-induced cardiotoxicity. In isolated murine cardiomyocytes, CA showed a concentration-dependent cytoprotective effect against Dox. Dox treatment significantly (p < 0.01) increased the formation of reactive oxygen species (ROS), increased NO levels, activated NADPH oxidase, and inactivated the cellular redox defense mechanism in cardiac cells, resulting in augmented oxidative stress in cardiomyocytes and rat hearts. Dox-induced oxidative stress significantly (p < 0.01) upregulated several pathogenic signal transductions, which induced apoptosis, inflammation, and fibrosis in cardiomyocytes and murine hearts. In contrast, CA significantly (p < 0.05-0.01) reciprocated Dox-induced cardiac apoptosis, inflammation, and fibrosis by suppressing oxidative stress and interfering with pathological signaling events in both isolated murine cardiomyocytes and rat hearts. CA treatment significantly (p < 0.05-0.01) countered Dox-mediated pathological changes in blood parameters in rats. Histological examinations backed up the pharmacological findings. In silico chemometric investigations predicted potential interactions between CA and studied signal proteins, as well as the drug-like features of CA. Thus, it would be concluded that CA has the potential to be regarded as an effective agent to alleviate Dox-mediated cardiotoxicity in the future.

Melatonin counteracts necroptosis and pulmonary edema in cadmium-induced chronic lung injury through the inhibition of angiotensin II

The renin-angiotensin system (RAS) is an important regulator in pulmonary physiology. In our study, we identified the efficacy of melatonin to control the RAS in cadmium (Cd) induced chronic lung injury in a mouse model. Swiss albino mice exposed to CdCl₂ intraperitoneally (I.P.) (1 mg/kg b.w.; 12 weeks) showed increased release of lactate dehydrogenase in bronchoalveolar lavage fluid, generating reactive oxygen species, impaired antioxidant enzymes function, and disrupted alveolar structure along with increased expression of Angiotensin-II (Ang-II) in lung tissue. Cd-induced angiotensin-converting enzyme-2-Ang-II axis imbalance triggered the onset of Ang-II induced tumour necrosis factor alpha  (TNF-α) mediated necroptosis by upregulating the signalling molecules RIP-1, RIP-3, and p-mixed lineage kinase domain-like. In an in vitro study, colocalization of Ang-II-RIP-3 molecule in Cd intoxicated L-132 cells (human alveolar epithelial cell line), as well as pretreatment of Cd exposed cells with the inhibitor's captopril (10 μM), necrostatin-1 (50 μM), and etanercept (5 μg/ml) indicated TNF-α induced necroptotic cell death via activation of the key molecule, Ang-II. Moreover, Ang-II disrupted the alveolar-capillary barrier by decreasing tight junctional proteins (zonula occludens-1 and occludin) and endothelial VE-cadherin expression. The use of human umbilical vein endothelial cells as a model of junctional protein-expressing cells showed that captopril pretreatment (25 μM) restored VE-cadherin expression in Cd-treated human umbilical vein endothelial cells. In CdCl₂ intoxicated mice, melatonin pretreatment (10 mg/kg b.w.; 12 weeks, I.P.) inhibited inflammatory mediators (TNF-α, interleukin [IL]-1β, and IL-6) release and effectively suppressed (Cd-induced) Ang-II mediated necroptotic cell death and alveolar-capillary breaching due to Cd toxicity.

ROS-Influenced Regulatory Cross-Talk With Wnt Signaling Pathway During Perinatal Development

Over a century ago, it was found that a rapid burst of oxygen is needed and produced by the sea urchin oocyte to activate fertilization and block polyspermy. Since then, scientific research has taken strides to establish that Reactive Oxygen Species (ROS), besides being toxic effectors of cellular damage and death, also act as molecular messengers in important developmental signaling cascades, thereby modulating them. Wnt signaling pathway is one such developmental pathway, which has significant effects on growth, proliferation, and differentiation of cells at the earliest embryonic stages of an organism, apart from being significant role-players in the instances of cellular transformation and cancer when this tightly-regulated system encounters aberrations. In this review, we discuss more about the Wnt and ROS signaling pathways, how they function, what roles they play overall in animals, and mostly about how these two major signaling systems cross paths and interplay in mediating major cellular signals and executing the predestined changes during the perinatal condition, in a systematic manner.

Synthesis of carbon dots from taurine as bioimaging agent and nanohybrid with ceria for antioxidant and antibacterial applications

Here we have synthesized water soluble and biocompatible carbon dots (CDs) from taurine via thermal decomposition method. The CDs showed nearly spherical shape with diameter less than 10 nm. The CDs exhibited excitation dependent fluorescence emission and could be used for mammalian cell imaging. The CDs showed excellent DPPH and hydrogen peroxide radical scavenging activity in cell free system. Besides, the CDs also displayed significant intracellular radical scavenging activity in human normal kidney epithelial (NKE) cells. Furthermore, nanohybrids consisting of both CDs and nanoceria (CeO₂) were prepared and tested for their biomedical applications. The nanohybrids showed significant antioxidant activities in both cell free and intracellular conditions. The CDs and nanohybrids possessed very little toxicity upto the concentration of 100 μg/mL when treated for 24 hours in human NKE cells. The CDs as well as nanohybrids further displayed significant bacterial growth inhibition against both gram-positive and gram-negative bacteria under dark as well as light illumination condition via the bacterial membrane damage. However, under the light illumination, the bacterial growth inhibition of CDs and nanohybrids was further enhanced due to the generation of reactive oxygen radicals and subsequent DNA degradation. A higher dose-dependent intracellular antioxidant and antibacterial activities of the nanohybrid is attributed to the synergistic effect of nanoceria and CDs. All these results clearly reflected that our synthesized CDs and their nanohybrids can be used for several biomedical applications.