Rabindranath Tagore University formerly AISECT University is a premier private university established by All India Society for Electronics & Computer Technology in Mendua Village in Raisen District, Bhopal, Madhya Pradesh, India. and has a Branch in Bhopal. Rabindranath Tagore University is recognised by University Grant Commission and the Madhya Pradesh State Government. It provides academic programmes in graduate, post graduate and research levels in Engineering, Information Technology, Management, Law, Science, Arts, Commerce, Education, Paramedical etc. AISECT Academy for Fire, Safety & Security was launched with the support of NAFS– National Academy of Fire & Safety Engineering.
This study investigates the synthesis and evaluation of glycine-conjugated 5.0G polypropyleneimine dendrimers as an advanced nanocarrier system for the selective delivery of chloroquine. 5.0G PPI dendrimers were synthesized via a divergent method and subsequently conjugated with glycine. Comprehensive characterization confirmed the successful modification and an increase in nanocarrier size. Drug loading studies demonstrated a significantly enhanced entrapment of chloroquine (57.5
Aspect Based Sentiment Analysis (ABSA) has emerged as a crucial research area in Natural Language Processing (NLP), offering fine-grained insights into opinions by identifying sentiment towards specific aspects of a given entity. This paper presents a comprehensive overview of ABSA, detailing the interactions between core components such as aspect term extraction, sentiment classification, opinion-target association, and domain adaptation. By tracing the evolution of sentiment analysis from early machine learning techniques to contemporary transformer-based models such as BERT, RoBERTa, and GPT, the paper provides a clear framework for understanding the progression of the field. A systematic categorization of ABSA’s fundamental components is offered, alongside an in-depth discussion of datasets and benchmarking strategies commonly used in ABSA research. Applications in industries such as e-commerce, healthcare, finance, education, and social networks are explored, with particular attention to the role of ABSA in distinguishing human-generated and AI-generated content. We have also identified and addressed significant challenges in ABSA, including managing implicit aspects, handling sentiment drift, developing multilingual and code-mixed solutions, and scaling for real-world deployment. Actionable recommendations emphasize the integration of ABSA with explainable AI, multimodal sentiment analysis, and prompt-based learning to advance the field. To the best of our knowledge, this is the first comprehensive state-of-the-art review on ABSA. The paper concludes with insights into future research directions, highlighting the need for innovative approaches to overcome current limitations and harness ABSA’s full potential in large-scale industrial applications, which might serve as a valuable resource for researchers and practitioners aiming to develop robust, accurate, and adaptable sentiment analysis systems.
To develop and evaluate a novel chitosan-coated submicron emulsion (SubE) incorporating a ciprofloxacin-potassium sorbate (CIF-PoS) ionic complex for improved ocular drug delivery, addressing limitations of conventional eye drops such as poor corneal retention and bioavailability. The CIF-PoS complex was prepared via ion-pairing at optimized molar ratios and pH, characterized by ¹H NMR. SubEs were formulated using high-energy emulsification with egg lecithin, Pluronic F-68®, and chitosan. Physicochemical properties (droplet size, zeta potential, viscosity, encapsulation efficiency) were assessed. In vitro release was studied via dialysis. Ex vivo antimicrobial efficacy against Pseudomonas aeruginosa biofilms was evaluated using MIC/MBC assays. In vivo corneal retention was examined in Wistar rats using fluorescence microscopy and HPLC-MS for pharmacokinetics. Stability was tested per ICH guidelines. The optimized SubE-CN-CIF-PoS exhibited a droplet size of 227.1 ± 5.6 nm and a polydispersity index (PdI) of 0.24 ± 0.03, + 33.2 mV zeta potential, 91.43
Next generation sequencing (NGS) remains underutilized in clinical microbiology applications despite providing broad pathogen spectrum detection superior to other molecular methods. This is primarily because of lower sensitivity of metagenomic NGS (mNGS) compared to PCR, lengthy turn-around times, cost, and complexity of data analysis. Capture sequencing is a technique that can mitigate some of the limitations of mNGS. Using probes that are engineered to selectively bind and pull down desired nucleic acids, capture sequencing enriches for targets of interest and can result in up to a 10,000-fold increase in sensitivity compared to mNGS. In this study, we describe the application of capture sequencing on Oxford Nanopore Technology’s portable sequencer, the MinION MK1C. We examined the performance of VirCapSeq-VERT and TBDCapSeq, two distinct capture sequencing assays that target vertebrate viruses and tick-borne pathogens, respectively. Both assays were originally established on the Illumina platform. To enable sequencing on the MinION instrument, we developed a modified hybrid workflow using our established library preparation and capture protocol for Illumina, followed by the addition of the ONT sequencing adaptor. In tests using contrived and clinical samples, we compared sensitivity thresholds and sequencing output, including pathogen genome coverage and relevant read counts. The addition of capture enrichment to MinION NGS provided significant improvement in pathogen detection when compared to mNGS. Assessment of assay performance on pathogen-positive samples revealed equivalent sensitivity on the MinION MK1C and Illumina NextSeq. We found that the elevated read counts and sequencing depth generated by Illumina NGS were offset by the greater read length obtained on the MinION MK1C and resulted in comparable pathogen genome coverage between the two platforms. This study demonstrates the utility for employment of VirCapSeq and TBDCapSeq on different sequencing platforms and suggest the potential of the MinION platform for broad-spectrum clinical diagnostics.
The present review critically synthesizes electrochemical technologies for early detection of food allergens and spoilage biomarkers, addressing critical gaps in the food safety paradigms. Unlike previous reviews, this work uniquely integrates both topics under a unified framework, demonstrating shared analytical challenges including matrix interference, cross-reactivity, and field deployment while proposing solutions through nanomaterial modifications and molecularly imprinted polymers (MIPs) aspects. Globalization intensifies and encourages the food diversity, necessitating rapid, sensitive, and portable detection methods. The review systematically compares amperometric, voltammetric, and impedimetric techniques across diverse food matrices, providing quantitative benchmarks (detection limits, response times, matrix effects), which are currently very rarely available in the existing literature. Advanced nanomaterials such as graphene, CNTs, MOFs, and MIPs enhances sensor selectivity, sensitivity, and stability in the complex environments milieu. Through case studies spanning smart packaging, portable devices, and IoT monitoring, this review demonstrates translational potential in the real-world applications. Critical analysis identifies persistent challenges and limits multi-analyte capabilities, regulatory barriers, and field validation gaps and challenges. We propose the electrode array designs, international harmonization frameworks, and industry-academia collaborations aspects. It is with the amalgamation of allergen-spoilage monitoring matters and shared detection chemistries, overlapping vulnerabilities, unified regulatory frameworks. this review provides a strategic insights for the advancement in the global food security through recent research synthesis.
