Nutraceuticals as Potential Therapeutic Agents for Colon Cancer: A Review

Colon cancer is a world-wide health problem and the second-most dangerous type of cancer, affecting both men and women. The modern diet and lifestyles, with high meat consumption and excessive alcohol use, along with limited physical activity has led to an increasing mortality rate for colon cancer worldwide. As a result, there is a need to develop novel and environmentally benign drug therapies for colon cancer. Currently, nutraceuticals play an increasingly important role in the treatment of various chronic diseases such as colon cancer, diabetes and Alzheimer׳s disease. Nutraceuticals are derived from various natural sources such as medicinal plants, marine organisms, vegetables and fruits. Nutraceuticals have shown the potential to reduce the risk of colon cancer and slow its progression. These dietary substances target different molecular aspects of colon cancer development. Accordingly, this review briefly discusses the medicinal importance of nutraceuticals and their ability to reduce the risk of colorectal carcinogenesis

Benzyl Isothiocyanate potentiates p53 signaling and antitumor effects against breast cancer through activation of p53-LKB1 and p73-LKB1 axes.

Functional reactivation of p53 pathway, although arduous, can potentially provide a broad-based strategy for cancer therapy owing to frequent p53 inactivation in human cancer. Using a phosphoprotein-screening array, we found that Benzyl Isothiocynate, (BITC) increases p53 phosphorylation in breast cancer cells and reveal an important role of ERK and PRAS40/MDM2 in BITC-mediated p53 activation. We show that BITC rescues and activates p53-signaling network and inhibits growth of p53-mutant cells. Mechanistically, BITC induces p73 expression in p53-mutant cells, disrupts the interaction of p73 and mutant-p53, thereby releasing p73 from sequestration and allowing it to be transcriptionally active. Furthermore, BITC-induced p53 and p73 axes converge on tumor-suppressor LKB1 which is transcriptionally upregulated by p53 and p73 in p53-wild-type and p53-mutant cells respectively; and in a feed-forward mechanism, LKB1 tethers with p53 and p73 to get recruited to p53-responsive promoters. Analyses of BITC-treated xenografts using LKB1-null cells corroborate in vitro mechanistic findings and establish LKB1 as the key node whereby BITC potentiates as well as rescues p53-pathway in p53-wild-type as well as p53-mutant cells. These data provide first in vitro and in vivo evidence of the integral role of previously unrecognized crosstalk between BITC, p53/LKB1 and p73/LKB1 axes in breast tumor growth-inhibition

Ayurvedic mediated green synthesis of gold and silver nanoparticles from marine microalgae Isochrysis sp.

Ayurveda is an Indian traditional medicinal system. Yet Ayurveda remains in living tradition. There has been an increased global interest in traditional medicine systems. Asavas is a novel yet less exploited hydro extraction method in Ayurveda. As green synthesis of metal nanoparticles is widely under exploration in the current research world, synthesis of gold and silver nanoparticles by employing the Ayurveda method using marine microalgae is tested in this research. The characterization of metal nanoparticles was confirmed by UV- Visible Spectroscopy, field emission scanning electron microscopy (FESEM), and Fourier transform infrared spectroscopy (FT-IR). Through the Arishtas method, gold and silver nanoparticles were successfully isolated from Isochrysis sp. The synthesized nanoparticles exhibit excellent antioxidant and antimicrobial activities

HO-3867, a STAT3 inhibitor induces apoptosis by inactivation of STAT3 activity in BRCA1-mutated ovarian cancer cells

BRCA1 plays an important role in DNA damage and repair, homologous recombination, cell-cycle regulation and apoptosis. BRCA-mutated ovarian cancer often presents at an advanced stage, however, tend to have better response to platinum-based chemotherapy as compared with sporadic cases of epithelial ovarian cancer (EOC). In spite of this, most patients will develop a recurrence and eventually succumb to the disease. Preclinical studies are currently investigating natural compounds and their analogs for tumor-directed targets in ovarian cancer. The aim of this study is to investigate whether the STAT3 inhibitor HO-3867, a novel curcumin analog, has a therapeutic effect on BRCA1-mutated ovarian cancer. Our novel agent, HO-3867 and a commercial STAT3 inhibitor, STATTIC, significantly inhibited BRCA-mutated ovarian cancer cells in vitro in a dose- and time-dependent manner. BRCA-mutated ovarian cancer cells treated with HO-3867 exhibited a significant degree of apoptosis with elevated levels of cleaved caspase-3, caspase-7 and PARP. HO-3867 treatment induced more reactive oxygen species (ROS) in BRCA-mutated cells compared with wild-type cells, however, there was no increased ROS when benign ovarian surface epithelial cells were treated with HO-3867. BRCA1-mutated cancer cells had higher expression of Tyrosine-phosphorylated STAT3 (pTyr705) as compared with other STAT proteins. Furthermore, treatment of these cells with HO-3867 resulted in decreased expression of pTyr705 and its downstream targets cyclin D1, Bcl-2 and survivin. In addition, overexpression of STAT3 cDNA provided resistance to HO-3867-induced apoptosis. Our results show that HO-3867, a potent STAT3 inhibitor, may have a role as a biologically targeted agent for BRCA1-mutated cancers either as an adjunct to cytotoxic chemotherapy or as a single agent

Cholic Acid-Based Antimicrobial Peptide Mimics as Antibacterial Agents

There is a significant and urgent need for the development of novel antibacterial agents to tackle the increasing incidence of antibiotic resistance. Cholic acid-based small molecular antimicrobial peptide mimics are reported as potential new leads to treat bacterial infection. Here, we describe the design, synthesis and biological evaluation of cholic acid-based small molecular antimicrobial peptide mimics. The synthesis of cholic acid analogues involves the attachment of a hydrophobic moiety at the carboxyl terminal of the cholic acid scaffold, followed by the installation of one to three amino acid residues on the hydroxyl groups present on the cholic acid scaffold. Structure–activity relationship studies suggest that the tryptophan moiety is important for high antibacterial activity. Moreover, a minimum of +2 charge is also important for antimicrobial activity. In particular, analogues containing lysine-like residues showed the highest antibacterial potency against Gram-positive S. aureus. All di-substituted analogues possess high antimicrobial activity against both Gram-positive S. aureus as well as Gram-negative E. coli and P. aeruginosa. Analogues 17c and 17d with a combination of these features were found to be the most potent in this study. These compounds were able to depolarise the bacterial membrane, suggesting that they are potential antimicrobial pore forming agents

Automated Security Analysis of IoT Software Updates

IoT devices often operate unsupervised in ever-changing environments for several years. Therefore, they need to be updated on a regular basis. Current approaches for software updates on IoT, like the recent SUIT proposal, focus on granting integrity and confidentiality but do not analyze the content of the software update, especially the IoT application which is deployed to IoT devices. To this aim, in this paper, we present IoTAV, an automated software analysis framework for systematically verifying the security of the applications contained in software updates w.r.t. a given security policy. Our proposal can be adopted transparently by current IoT software updates workflows. We prove the viability of IoTAV by testing our methodology on a set of actual RIOT OS applications. Experimental results indicate that the approach is viable in terms of both reliability and performance, leading to the identification of 26 security policy violations in 31 real-world RIOT applications

Sequential decarboxylative azide–alkyne cycloaddition and dehydrogenative coupling reactions: one-pot synthesis of polycyclic fused triazoles

Herein, we describe a one-pot protocol for the synthesis of a novel series of polycyclic triazole derivatives. Transition metal-catalyzed decarboxylative CuAAC and dehydrogenative cross coupling reactions are combined in a single flask and achieved good yields of the respective triazoles (up to 97% yield). This methodology is more convenient to produce the complex polycyclic molecules in a simple way

Sentiment analysis on COVID-19 Twitter data streams using deep belief neural networks

Social media is Internet-based by design, allowing people to share content quickly via electronic means. People can openly express their thoughts on social media sites such as Twitter, which can then be shared with other people. During the recent COVID-19 outbreak, public opinion analytics provided useful information for determining the best public health response. At the same time, the dissemination of misinformation, aided by social media and other digital platforms, has proven to be a greater threat to global public health than the virus itself, as the COVID-19 pandemic has shown. The public's feelings on social distancing can be discovered by analysing articulated messages from Twitter. The automated method of recognizing and classifying subjective information in text data is known as sentiment analysis. In this research work, we have proposed to use a combination of preprocessing approaches such as tokenization, filtering, stemming, and building N-gram models. Deep belief neural network (DBN) with pseudo labelling is used to classify the tweets. Top layers of the base classifiers are boosted in the pseudo labelling strategy, whereas lower levels of the base classifiers share weights for feature extraction. By introducing the pseudo boost mechanism, our suggested technique preserves the same time complexity as a DBN while achieving fast convergence to optimality. The pseudo labelling improves the performance of the classification. It extracts the keywords from the tweets with high precision. The results reveal that using the DBN classifier in conjunction with the bigram in the N-gram model outperformed other models by 90.3 percent. The proposed approach can also aid medical professionals and decision-makers in determining the best course of action for each location based on their views regarding the pandemic