Jha, Sushmita

Gliomas are the most prevalent primary brain tumors with immense clinical heterogeneity, poor prognosis and survival. The nucleotide-binding domain, and leucine-rich repeat containing receptors (NLRs) and absent-in-melanoma 2 (AIM2) are innate immune receptors crucial for initiation and progression of several cancers. There is a dearth of reports linking NLRs and AIM2 to glioma pathology. NLRs are expressed by cells of innate immunity, including monocytes, macrophages, dendritic cells, endothelial cells, and neutrophils, as well as cells of the adaptive immune system. NLRs are critical regulators of major inflammation, cell death, immune and cancer-associated pathways. We used a data-driven approach to identify NLRs, AIM2 and NLR-associated gene expression and methylation patterns in low grade glioma and glioblastoma, using The Cancer Genome Atlas (TCGA) patient datasets. Since TCGA data is obtained from tumor tissue, comprising of multiple cell populations including glioma cells, endothelial cells and tumor-associated microglia/macrophages we have used multiple cell lines and human brain tissues to identify cell-specific effects. TCGA data mining showed significant differential NLR regulation and strong correlation with survival in different grades of glioma. We report differential expression and methylation of NLRs in glioma, followed by NLRP12 identification as a candidate prognostic marker for glioma progression. We found that Nlrp12 deficient microglia show increased colony formation while Nlrp12 deficient glioma cells show decreased cellular proliferation. Immunohistochemistry of human glioma tissue shows increased NLRP12 expression. Interestingly, microglia show reduced migration towards Nlrp12 deficient glioma cells.

Nucleotide binding domain, leucine-rich repeat containing proteins (NLRs) are a family of pattern recognition receptors involved in major innate immune defense mechanisms. NLRs play a key role in several cancers, autoimmune, and inflammation-associated diseases. Association of NLRP3 has been widely investigated in neurodegenerative diseases, chronic alcoholism, depression, traumatic brain injury, and pathogenic infections. Several research studies have shown possible involvement of various other inflammasome-forming and non-inflammasome-forming NLRs in the brain; however, their mechanisms of action are yet to be defined clearly. Our review provides a comprehensive overview of the expression of NLRs in human brain and their critical association with inflammation and neurodegenerative diseases. The review also summarizes promising NLR-targeted therapeutics and their prospects for brain pathologies.

Chitin membranes containing nanosilver were evaluated for use as antimicrobial wound dressings. Chitin at a concentration of 0.25% dissolved in 5% lithium chloride-dimethylacetamide and nanosilver synthesized by gamma irradiation were used for fabrication of chitin-nanosilver membranes. UV-vis spectroscopy and energy dispersive x-ray (EDX) analysis with scanning electron microscopy (SEM) were used to confirm the presence of silver nanoparticles. Fluid absorption capacity, moisture vapour transmission rate, antimicrobial activity, effect on cell viability, in vitro wound healing property and the silver elution profile were determined, to assess the wound dressing properties of the chitin-nanosilver membranes. The antimicrobial efficacy of chitin membranes containing silver nanoparticles was observed against a broad range of microbes such as Acinetobacter baumanii, Enterobacter cloacae, Escherichia coli, Klebsiella pneumoniae, Proteus vulgaris and Candida albicans. The chitin-nanosilver membranes prepared with 100 ppm silver resulted in 6-log to 8-log reduction in viable counts after 24 h and had a positive impact on fibroblast proliferation. The fluid handling capacity, cell viability test and silver elution profile indicate that the chitin-nanosilver dressing can contribute to effective management of infected wounds. In vitro studies have demonstrated the antimicrobial activity and wound-healing properties of chitin membranes containing nanosilver.

Exploring the symbiotic nature of biological systems can result in valuable knowledge for computer networks. Biologically inspired approaches to security in networks are interesting to evaluate because of the analogies between network security and survival of human body under pathogenic attacks. Wireless Sensor Network (WSN) is a network based on multiple low-cost, low-energy sensor nodes connected to physical signals. The network is made up of sensor nodes and gateways, where the server nodes acquire physical world data, while the gateway forwards the data to the end-user. While the spread of viruses in wired systems has been studied in-depth, applying trust in wireless sensor network nodes is an emerging area. This paper uses machine learning techniques to first differentiate between fraudulent and good nodes in the system. Next, it derives inspiration from the human immune system to present an idea of virtual antibodies in the system, to disable the fraudulent nodes in the system. © 2013 IEEE.

The inflammasome is a large multimeric protein complex comprising an effector protein that demonstrates specificity for a variety of activators or ligands; an adaptor molecule; and procaspase-1, which is converted to caspase-1 upon inflammasome activation. Inflammasomes are expressed primarily by myeloid cells and are located within the cell. The macromolecular inflammasome structure can be visualized by cryo-electron microscopy. This complex has been found to play a role in a variety of disease models in mice, and several have been genetically linked to human diseases. In most cases, the effector protein is a member of the NLR (nucleotide-binding domain leucine-rich repeat-containing) or NOD (nucleotide oligomerization domain)-like receptor protein family. However, other effectors have also been described, with the most notable being AIM-2 (absent in melanoma 2), which recognizes DNA to elicit inflammasome function. This review will focus on the role of the inflammasome in myeloid cells and its role in health and disease.

NLRs (nucleotide-binding domain, leucine-rich repeat containing receptors) are pattern recognition receptors associated with immunity and inflammation in response to endogenous and exogenous pathogen and damage associated molecular patterns (PAMPs and DAMPs respectively). Dysregulated NLR function is associated with several diseases including cancers, metabolic diseases, autoimmune disorders and autoinflammatory syndromes. In the last decade, distinct cell and organ specific roles for NLRs have been identified however; their roles in cancer initiation, development and progression remain controversial. This review summarizes the emerging role of NLRs in cancer and their possible future as targets for cancer therapeutics.

Inflammation is the body’s response to injury, pathogen exposure, and irritants. Pattern recognition receptors allow our body to recognize a diverse array of patterns generated during exposure to these insults. In 2002, thenucleotide-binding domainleucine-richrepeat-containing (NLR, also known as NOD-like receptor) gene family of pattern recognition receptors was discovered (1-3). While several members were already recognized at that point, reports of the entire NLR family provided a global view. In the past 15 years of research, the physiological relevance of these genes has been revealed to include a diverse variety of functions. Gene mutations in some of the family members have been linked to autoinflammatory diseases in humans (Fig. 1). This association of mutations in NLR genes to autoinflammatory diseases indicates critical functions in the regulation of immunity and inflammation.

Gliomas are the most common solid tumors among central nervous system tumors. Most glioma patients succumb to their disease within two years of the initial diagnosis. The median survival of gliomas is only 14.6 months, even after aggressive therapy with surgery, radiation, and chemotherapy. Gliomas are heavily infiltrated with myeloid- derived cells and endothelial cells. Increasing evidence suggests that these myeloid- derived cells interact with tumor cells promoting their growth and migration. NLRs (nucleotide-binding oligomerization domain (NOD)-containing protein like receptors) are a class of pattern recognition receptors that are critical to sensing pathogen and danger associated molecular patterns. Mutations in some NLRs lead to autoinflammatory diseases in humans. Moreover, dysregulated NLR signaling is central to the pathogenesis of several cancers, autoimmune and neurodegenerative diseases. Our review explores the role of angiogenic factors that contribute to upstream or downstream signaling pathways leading to NLRs. Angiogenesis plays a significant role in the pathogenesis of variety of tumors including gliomas. Though NLRs have been detected in several cancers including gliomas and NLR signaling contributes to angiogenesis, the exact role and mechanism of involvement of NLRs in glioma angiogenesis remain largely unexplored. We discuss cellular, molecular and genetic studies of NLR signaling and convergence of NLR signaling pathways with angiogenesis signaling in gliomas. This may lead to re-appropriation of existing anti-angiogenic therapies or development of future strategies for targeted therapeutics in gliomas.

Exploring the symbiotic nature of biological systems can result in valuable knowledge for computer networks. Biologically inspired approaches to security in networks are interesting to evaluate because of the analogies between network security and survival of human body under pathogenic attacks. Wireless Sensor Network (WSN) is a network based on multiple low-cost communication and computing devices connected to sensor nodes which sense physical parameters. While the spread of viruses in wired systems has been studied in-depth, applying trust in WSN is an emerging research area. Security threats can be introduced in WSN through various means, such as a benevolent sensor node turning fraudulent after a certain period of time. The proposed research work uses biological inspirations and machine learning techniques for adding security against such threats. While it uses machine learning techniques to identify the fraudulent nodes, consecutively by deriving inspiration from human immune system it effectively nullify the impact of the fraudulent ones on the network. Proposed work has been implemented in LabVIEW platform and obtained results that demonstrate the accuracy, robustness of the proposed model. © 2014 IEEE.

Trigonella foenum-graecum (fenugreek) is an important medicinal plant, well known for its antiinflammatory properties. However, the underlying cellular and molecular mechanisms of its action remain largely unknown. The apoptosis associated speck like protein containing a caspase recruitment domain (CARD) (ASC) is central to inflammatory and cell death pathways in innate and adaptive immunity. Here, we show that fenugreek seed extract provides cytoprotection to bacterial lipopolysaccharide (LPS) inflammed and nanosilica-treated fibroblasts via a reactive oxygen species independent pathway. All atom molecular dynamics simulations of ASC-ligand complex reveal that individual phytochemicals in fenugreek can bind to ASC via specific non-covalent interactions. These data show that a synergistic effect of fenugreek phytochemicals with the ASC protein alters its molecular properties resulting in altered cellular function. Such information is crucial to the development of targeted therapeutic interventions for inflammatory diseases.