Differential expression of tear film cytokines in Stevens–Johnson syndrome patients and comparative review of literature

To investigate the differential expression of tear cytokine levels among chronic Stevens–Johnson syndrome (SJS) patients to better understand the role of significantly altered cytokines in disease development. Tear samples were collected using Schirmer strips in 24 eyes of chronic SJS, 24 eyes of age and gender-matched controls, and 14 eyes of aqueous deficiency dry eye disease (DED) patients. The cytokine analysis was performed among 18 analytes which include pro-inflammatory, anti-inflammatory factors, and ELR-negative CXC chemokines. String analysis was performed for the significantly altered cytokines to understand their co-expression and role in the disease development. Additionally, a literature review was conducted to identify the signature cytokines present in chronic SJS tears. The differential expression of IL-6 (p ≤ 0.029), CXCL8/IL-8 (p ≤ 0.009), IL-1β (p ≤ 0.041), IL-2 (p ≤ 0.025), IL-10 (p ≤ 0.053), and CXCL-10 (p ≤ 0.044) were observed in chronic SJS patients and healthy controls. Whereas, IL-6 (p ≤ 0.029), CXCL8/IL-8 (p ≤ 0.058), CCL4 (p ≤ 0.056), GM-CSF (p ≤ 0.0001) IL-10 (p ≤ 0.025), and CXCL-10 (p ≤ 0.010), were differentially expressed in SJS as compared to severe DED patients. String analysis of the significantly altered cytokines revealed the involvement of several biological processes including the chronic inflammatory response, nitric oxide synthesis, angiogenesis, and cellular response to drugs. Among all the cytokines evaluated, the expression of CXCL8/IL-8 and CXCL10 levels were consistently reported in the literature. There was a differential expression of tear cytokines in SJS when compared to DED and healthy controls. The differential expression of CXCL8/IL-8 and CXCL10 was in line with existing literature and their role in chronic SJS pathogenesis merits further evaluation.

String Analysis to identify the Activity of Gyrinops versteegii derived Lauric Acid against Breast Cancer

Understanding the interactions between cellular proteins and compounds from agarwood (Gyrinops versteegii) could lead to effective approaches for the diagnosis and treatment of breast cancer. In this study, we aimed to identify the interaction between lauric acid, a compound derived from agarwood (G. versteegii) and its target proteins using String database analysis. String analysis showed that lauric acid affects cellular proliferation through interactions with the Androgen Receptor (AR) and binds to Aldo-Keto Reductase (AKR1C3). Lauric acid also interacted with mitogen-activated protein kinase 1 (MAPK1) and other proteins such as matrix metalloprotein (MMP2), chemokine (CXCL8), B-cell lymphoma protein (BCL2). Retinoid Acid Receptor (RARG) and Androgen Receptor (AR) sub network are bridging system of regulation in breast cancer molecular process. These results show that lauric acid may interact with many proteins by AR sub network to increase apoptosis and reduce cancer cell proliferation. These results show that lauric acid may interact with many proteins to increase apoptosis and reduce cancer cell proliferation.

Systematic Identification of Protein Targets of Sub5 Using Saccharomyces cerevisiae Proteome Microarrays

Antimicrobial peptides (AMPs) are intensively studied in terms of alternative drugs. Sub5 is a synthetic 12-mer AMP with substitutions of five amino acids of bactenecin 2A (Bac2A), a linear-ized bactenecin variant of bovine. Sub5 is highly effective against fungi with an ability to trans-locate cell membrane, but its targets are unknown. Systematic analysis of Sub5 targets will facil-itate our understanding on its mechanism of action. In this study, we used high-throughput Saccharomyces cerevisiae proteome microarrays to explore the potential protein targets of Sub5. The screening results showed 128 potential protein targets of Sub5. Bioinformatics analysis of protein targets of Sub5 revealed significant gene ontology (GO) enrichment in actin related pro-cess of “actin filament-based process”, “actin filament organization”, “actin cortical patch or-ganization”, regulation of “actin filament bundle assembly”. Moreover, the other enriched cat-egories in GO enrichment mostly contained actin associate proteins. In total, 11 actin-associated proteins were identified in the protein targets of Sub5. Protein family (PFAM) enrichment anal-ysis shows protein domain enriched in actin binding, i.e., “Cytoskeletal-regulatory complex EF hand (helix E-loop-helix F motif)”. Being consistent with GO analysis, Search Tool for the Re-trieval of Interacting Genes/Proteins (STRING) analysis of the protein targets of Sub5 showed ac-tin network with involvement of 15 protein targets. Along with actin-network, STRING analysis showed protein–protein interaction network in ribonucleoprotein, transcription and translation, chromosome, histone, and ubiquitin related, DNA repair, and chaperone. Multiple Expression motifs for Motif Elicitation (MEME) suite provided a consensus binding motif of [ED][ED]EEE[ED][ED][ED][ED][ED], in total of 75 protein targets of Sub5. This motif was present in 9 out of 15 actin-related proteins identified among protein targets of Sub5.

In-Vitro antioxidant, anti-lipid peroxidative activities and In-Silico study of Terminalia chebula bioactive compounds

Objective To evaluate the antioxidant activities and to identify the bioactive compounds in hot water extracts of Terminalia chebula fruit. Methods The antioxidant activities were determined by DPPH assay, lipid peroxidation assay, iron chelation and total antioxidant assay. The phenolic composition was determined by HPLC-DAD. Human Rab8b Protein was used for the validation of compounds as anti-inflammation. String analysis for protein synergism was used. Results The analysis of Terminalia chebula Retzius (Combretaceae) phenolics showed anti-inflammatory effect. The specific phenolic compositions were determined by high performance liquid chromatography (HPLC) and resulted in the identification of rutin, catechin, caffeic acid, gallicacid, ellagic acid, epicatechin, and quercetin as antioxidant compounds. Human Rab8b protein is selected for protein docking and all compounds except rutin showed good results. ADMET properties were checked by using AdmetSar and all seven compounds showed validation for AMET properties. The synergisms of compounds were analyzed by STRING analysis and our ligands shows strong binding with human Rab8b proteins. The aqueous extract was capable of inhibiting the lipid peroxidation in egg yolk phospholipid homogenate. The extract scavenged the 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) (IC50,71.5 ± 2.1 μg/ml). The extract displayed the high metal chelation activities and reducing abilities on the phosphomolybdenum assay. Conclusions It is concluded that extracts of T. chebula have good antioxidant and anti-inflammation activities and are rich in phenolics.

A Mathematical Model of HMST Model on Malware Static Analysis

Malware is a malicious software that can contaminate communication devices, where information can be lost, encrypting or deleting the sensitive data, altering or hijacking core computing activities and monitoring a user's computer activity without proper authorization. Analyzing the behavior of any new type of malware, that threatens the security of information is the challenging task. Previous studies and research has used static and dynamic based analysis. Althrough there are various methods to analysis the behaviour of the malware, the innovation of new technology lead to undesirable growth of malware. A procedure to analyze the characteristics and its nature is the need of the day. To mitigate this issue, malware specific procedures need to be evolved by analysing its behaviour. In this article, the authors present a heuristic-based malware static analysis testing (HMST) through a six step process including hash verification, PE structure analysis, packer signature analysis, entropy analysis, antivirus check and string analysis. Heuristic-based malware static analysis (MSA) depends on the six characterstics. The six characteristics sequence is quantified mathematially. Hash verification is presented as a dynamic function, PE structure analysis (PESA) as the functional string, Packer Signature (PS) by functional boundedness, Entropy Analysis (EA) with probability, antivirus check (AC) of the discrete lagorthm-bit representation and string analysis (SA) lies with the comutational complexity. Hence, an optimized string is proposed for transmitting securely. CFF Explorer, BinText, PeID, DIE and VirusTotal are used for analyzing the behavior of the samples in this study.